Dissertations / Theses on the topic 'Analytic Hilbert Spaces'
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Ameur, Yacin. "Interpolation of Hilbert spaces /." Uppsala : Matematiska institutionen, Univ. [distributör], 2001. http://publications.uu.se/theses/91-506-1531-9/.
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Harris, Terri Joan Mrs. "HILBERT SPACES AND FOURIER SERIES." CSUSB ScholarWorks, 2015. https://scholarworks.lib.csusb.edu/etd/244.
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I give an overview of the basic theory of Hilbert spaces necessary to understand the convergence of the Fourier series for square integrable functions. I state the necessary theorems and definitions to understand the formulations of the problem in a Hilbert space framework, and then I give some applications of the theory along the way.
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Lapinski, Felicia. "Hilbert spaces and the Spectral theorem." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-454412.
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Sorensen, Julian Karl. "White noise analysis and stochastic evolution equations." Title page, contents and abstract only, 2001. http://web4.library.adelaide.edu.au/theses/09PH/09phs713.pdf.
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Tipton, James Edward. "Reproducing Kernel Hilbert spaces and complex dynamics." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2284.
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Both complex dynamics and the theory of reproducing kernel Hilbert spaces have found widespread application over the last few decades. Although complex dynamics started over a century ago, the gravity of it's importance was only recently realized due to B.B. Mandelbrot's work in the 1980's. B.B. Mandelbrot demonstrated to the world that fractals, which are chaotic patterns containing a high degree of self-similarity, often times serve as better models to nature than conventional smooth models. The theory of reproducing kernel Hilbert spaces also having started over a century ago, didn't pick up until N. Aronszajn's classic was written in 1950. Since then, the theory has found widespread application to fields including machine learning, quantum mechanics, and harmonic analysis.
In the paper, Infinite Product Representations of Kernel Functions and Iterated Function Systems, the authors, D. Alpay, P. Jorgensen, I. Lewkowicz, and I. Martiziano, show how a kernel function can be constructed on an attracting set of an iterated function system. Furthermore, they show that when certain conditions are met, one can construct an orthonormal basis of the associated Hilbert space via certain pull-back and multiplier operators.
In this thesis we take for our iterated function system, the family of iterates of a given rational map. Thus we investigate for which rational maps their kernel construction holds as well as their orthornormal basis construction. We are able to show that the kernel construction applies to any rational map conjugate to a polynomial with an attracting fixed point at 0. Within such rational maps, we are able to find a family of polynomials for which the orthonormal basis construction holds. It is then natural to ask how the orthonormal basis changes as the polynomial within a given family varies. We are able to determine for certain families of polynomials, that the dynamics of the corresponding orthonormal basis is well behaved. Finally, we conclude with some possible avenues of future investigation.
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Giulini, Ilaria. "Generalization bounds for random samples in Hilbert spaces." Thesis, Paris, Ecole normale supérieure, 2015. http://www.theses.fr/2015ENSU0026/document.
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Ce travail de thèse porte sur l'obtention de bornes de généralisation pour des échantillons statistiques à valeur dans des espaces de Hilbert définis par des noyaux reproduisants. L'approche consiste à obtenir des bornes non asymptotiques indépendantes de la dimension dans des espaces de dimension finie, en utilisant des inégalités PAC-Bayesiennes liées à une perturbation Gaussienne du paramètre et à les étendre ensuite aux espaces de Hilbert séparables. On se pose dans un premier temps la question de l'estimation de l'opérateur de Gram à partir d'un échantillon i. i. d. par un estimateur robuste et on propose des bornes uniformes, sous des hypothèses faibles de moments. Ces résultats permettent de caractériser l'analyse en composantes principales indépendamment de la dimension et d'en proposer des variantes robustes. On propose ensuite un nouvel algorithme de clustering spectral. Au lieu de ne garder que la projection sur les premiers vecteurs propres, on calcule une itérée du Laplacian normalisé. Cette itération, justifiée par l'analyse du clustering en termes de chaînes de Markov, opère comme une version régularisée de la projection sur les premiers vecteurs propres et permet d'obtenir un algorithme dans lequel le nombre de clusters est déterminé automatiquement. On présente des bornes non asymptotiques concernant la convergence de cet algorithme, lorsque les points à classer forment un échantillon i. i. d. d'une loi à support compact dans un espace de Hilbert. Ces bornes sont déduites des bornes obtenues pour l'estimation d'un opérateur de Gram dans un espace de Hilbert. On termine par un aperçu de l'intérêt du clustering spectral dans le cadre de l'analyse d'imagesThis thesis focuses on obtaining generalization bounds for random samples in reproducing kernel Hilbert spaces. The approach consists in first obtaining non-asymptotic dimension-free bounds in finite-dimensional spaces using some PAC-Bayesian inequalities related to Gaussian perturbations and then in generalizing the results in a separable Hilbert space. We first investigate the question of estimating the Gram operator by a robust estimator from an i. i. d. sample and we present uniform bounds that hold under weak moment assumptions. These results allow us to qualify principal component analysis independently of the dimension of the ambient space and to propose stable versions of it. In the last part of the thesis we present a new algorithm for spectral clustering. It consists in replacing the projection on the eigenvectors associated with the largest eigenvalues of the Laplacian matrix by a power of the normalized Laplacian. This iteration, justified by the analysis of clustering in terms of Markov chains, performs a smooth truncation. We prove nonasymptotic bounds for the convergence of our spectral clustering algorithm applied to a random sample of points in a Hilbert space that are deduced from the bounds for the Gram operator in a Hilbert space. Experiments are done in the context of image analysis
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Awunganyi, John. "A study of optimization in Hilbert Space." CSUSB ScholarWorks, 1998. https://scholarworks.lib.csusb.edu/etd-project/1459.
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Zandler, Andersson Nils. "Boundedness of a Class of Hilbert Operators on Modulation Spaces." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-84932.
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In this work we take interest in frames and modulation spaces. On the basis of their properties, we show how frame expansions can be used to prove the boundedness of a particular class of Hilbert operators on modulation spaces taking advantage of the special category of piece-wise polynomial functions known as B-splines.
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Leon, Ralph Daniel. "Module structure of a Hilbert space." CSUSB ScholarWorks, 2003. https://scholarworks.lib.csusb.edu/etd-project/2469.
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This paper demonstrates the properties of a Hilbert structure. In order to have a Hilbert structure it is necessary to satisfy certain properties or axioms. The main body of the paper is centered on six questions that develop these ideas.
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Agora, Elona. "Boundedness of the Hilbert Transform on Weighted Lorentz Spaces." Doctoral thesis, Universitat de Barcelona, 2012. http://hdl.handle.net/10803/108930.
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The main goal of this thesis is to characterize the weak-type (resp. strong-type) boundedness of the Hilbert transform H on weighted Lorentz spaces Λpu(w). The characterization is given in terms of some geometric conditions on the weights u and w and the weak-type (resp. strong-type) boundedness of the Hardy-Littlewood maximal operator on the same spaces. Our results extend and unify simultaneously the theory of the boundedness of H on weighted Lebesgue spaces Lp(u) and Muckenhoupt weights Ap, and the theory on classical Lorentz spaces Λp(w) and Ariño-Muckenhoupt weights Bp.Títol: Acotaciò de l'operador de Hilbert sobre espais de Lorentz amb pesos Resum: L'objectiu principal d'aquesta tesi es caracteritzar l'acotació de l'operador de Hilbert sobre els espais de Lorentz amb pesos Λpu(w). També estudiem la versió dèbil. La caracterització es dona en terminis de condicions geomètriques sobre els pesos u i w, i l'acotació de l'operador maximal de Hardy-Littlewood sobre els mateixos espais. Els nostres resultats unifiquen dues teories conegudes i aparentment no relacionades entre elles, que tracten l'acotació de l'operador de Hilbert sobre els espais de Lebegue amb pesos Lp(u) per una banda i els espais de Lorentz clàssics Λp(w) per altre banda.
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Paiva, António R. C. "Reproducing kernel Hilbert spaces for point processes, with applications to neural activity analysis." [Gainesville, Fla.] : University of Florida, 2008. http://purl.fcla.edu/fcla/etd/UFE0022471.
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Al-Naggar, Ibtesam M. Abu-Sulayman. "Asymptotics for the solution of the Schrödinger equation." Thesis, University of Hull, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262439.
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Sabree, Aqeeb A. "Positive definite kernels, harmonic analysis, and boundary spaces: Drury-Arveson theory, and related." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/7023.
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A reproducing kernel Hilbert space (RKHS) is a Hilbert space $\mathscr{H}$ of functions with the property that the values $f(x)$ for $f \in \mathscr{H}$ are reproduced from the inner product in $\mathscr{H}$. Recent applications are found in stochastic processes (Ito Calculus), harmonic analysis, complex analysis, learning theory, and machine learning algorithms. This research began with the study of RKHSs to areas such as learning theory, sampling theory, and harmonic analysis. From the Moore-Aronszajn theorem, we have an explicit correspondence between reproducing kernel Hilbert spaces (RKHS) and reproducing kernel functions—also called positive definite kernels or positive definite functions. The focus here is on the duality between positive definite functions and their boundary spaces; these boundary spaces often lead to the study of Gaussian processes or Brownian motion. It is known that every reproducing kernel Hilbert space has an associated generalized boundary probability space. The Arveson (reproducing) kernel is $K(z,w) = \frac{1}{1-_{\C^d}}, z,w \in \B_d$, and Arveson showed, \cite{Arveson}, that the Arveson kernel does not follow the boundary analysis we were finding in other RKHS. Thus, we were led to define a new reproducing kernel on the unit ball in complex $n$-space, and naturally this lead to the study of a new reproducing kernel Hilbert space. This reproducing kernel Hilbert space stems from boundary analysis of the Arveson kernel. The construction of the new RKHS resolves the problem we faced while researching “natural” boundary spaces (for the Drury-Arveson RKHS) that yield boundary factorizations:
\[K(z,w) = \int_{\mathcal{B}} K^{\mathcal{B}}_z(b)\overline{K^{\mathcal{B}}_w(b)}d\mu(b), \;\;\; z,w \in \B_d \text{ and } b \in \mathcal{B} \tag*{\it{(Factorization of} $K$).}\]
Results from classical harmonic analysis on the disk (the Hardy space) are generalized and extended to the new RKHS. Particularly, our main theorem proves that, relaxing the criteria to the contractive property, we can do the generalization that Arveson's paper showed (criteria being an isometry) is not possible.
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Montgomery, Jason W. "Condition-dependent Hilbert Spaces for Steepest Descent and Application to the Tricomi Equation." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc699977/.
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A steepest descent method is constructed for the general setting of a linear differential equation paired with uniqueness-inducing conditions which might yield a generally overdetermined system. The method differs from traditional steepest descent methods by considering the conditions when defining the corresponding Sobolev space. The descent method converges to the unique solution to the differential equation so that change in condition values is minimal. The system has a solution if and only if the first iteration of steepest descent satisfies the system. The finite analogue of the descent method is applied to example problems involving finite difference equations. The well-posed problems include a singular ordinary differential equation and Laplace’s equation, each paired with respective Dirichlet-type conditions. The overdetermined problems include a first-order nonsingular ordinary differential equation with Dirichlet-type conditions and the wave equation with both Dirichlet and Neumann conditions. The method is applied in an investigation of the Tricomi equation, a long-studied equation which acts as a prototype of mixed partial differential equations and has application in transonic flow. The Tricomi equation has been studied for at least ninety years, yet necessary and sufficient conditions for existence and uniqueness of solutions on an arbitrary mixed domain remain unknown. The domains of interest are rectangular mixed domains. A new type of conditions is introduced. Ladder conditions take the uncommon approach of specifying information on the interior of a mixed domain. Specifically, function values are specified on the parabolic portion of a mixed domain. The remaining conditions are specified on the boundary. A conjecture is posed and states that ladder conditions are necessary and sufficient for existence and uniqueness of a solution to the Tricomi equation. Numerical experiments, produced by application of the descent method, provide strong evidence in support of the conjecture. Ladder conditions allow for a continuous deformation from Dirichlet conditions to initial-boundary value conditions. Such a deformation is applied to a class of Tricomi-type equations which transition from degenerate elliptic to degenerate hyperbolic. A conjecture is posed and states that each problem is uniquely solvable and the solutions vary continuously as the differential equation and corresponding conditions vary continuously. If the conjecture holds true, the result will provide a method of unifying elliptic Dirichlet problems and hyperbolic initial-boundary value problem. Numerical evidence in support of the conjecture is presented.
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Donnelly, Roderick Kerry Carleton University Dissertation Mathematics. "Some contributions to analysis; a new space of generalized functions for integro-differential equations involving Hilbert transforms, and a note on the non-nuclearity of a space of test functions on Hilbert space." Ottawa, 1987.
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Agrawal, Devanshu. "The Complete Structure of Linear and Nonlinear Deformations of Frames on a Hilbert Space." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3003.
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A frame is a possibly linearly dependent set of vectors in a Hilbert space that facilitates the decomposition and reconstruction of vectors. A Parseval frame is a frame that acts as its own dual frame. A Gabor frame comprises all translations and phase modulations of an appropriate window function. We show that the space of all frames on a Hilbert space indexed by a common measure space can be fibrated into orbits under the action of invertible linear deformations and that any maximal set of unitarily inequivalent Parseval frames is a complete set of representatives of the orbits. We show that all such frames are connected by transformations that are linear in the larger Hilbert space of square-integrable functions on the indexing space. We apply our results to frames on finite-dimensional Hilbert spaces and to the discretization of the Gabor frame with a band-limited window function.
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Grip, Niklas. "Hilbert space frames and bases : a comparison of Gabor and wavelet frames and applications to multicarrier digital communications." Licentiate thesis, Luleå tekniska universitet, Matematiska vetenskaper, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18012.
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Several signal processing applications today are based on the use of different transforms. The signals under consideration are written as a linear combination (or series) of some predefined set of functions. Traditionally, orthogonal bases have been used for this purpose, for example, in the discrete Fourier transform. The theory for orthogonal bases for Hilbert spaces can, however, be generalized to other sequences of functions, called frames. The first part of this thesis begins with an application-oriented introduction to the theory of frames and bases for separable Hilbert spaces. We explain similarities with and differences from the theory of orthogonal bases. Special attention is given to the relatively new theory of Gabor and Wavelet frames. We explain how they can be used for so-called time-frequency analysis. The main emphasis is on explaining fundamental similarities and differences between Gabor and wavelet frames. We also give an example of an application (OFDM) related to the second part of the thesis, for which nonorthogonal Gabor frames are superior to any orthogonal basis. The second part of this thesis concerns the current development of a standard for very high speed digital communication in ordinary telephone copper wires. It is the result of a cooperation with the Division of Signal Processing and Telia Research. We present a novel duplex method for Very high bitrate Digital Subscriber Lines (VDSL), called Zipper. It is intended to provide bit rates up to 52 Mbit per second, about 1000 times faster than the most common modems today. Zipper is based on Discrete Multi Tone (DMT) modulation. It uses an orthogonal basis of Gabor type for the signal transmission. Certain cyclical extensions are used to ensure the orthogonality between the basis functions. Zipper is proposed as a standard for VDSL to both the American National Standards Institute (ANSI) T1E1.4 group and in the European Telecommunication Standards Institute (ETSI) TM6 group. It will also be presented for the International Telecommunication Union (ITU). Telia Research is currently building a prototype together with ST Microelectronics (former SGS-Thomson), France. The first Zipper-VDSL modems are expected to be available on the mass market in the year 2001. The second part of this thext consists of a brief introduction to Zipper, an ANSI standard contribution and three conference papers. The standard contribution compares Zipper performance with competing standard proposals at that time: TDD and FDD. In the first conference paper we present a new and patented method for reducing the interference that the unshielded copper wires experience from radio transmissions. The two last conference papers present a low complexity method for reducing the so-called Peak to Average power Ratio (PAR) of the transmitted signal. PAR is a measure for the amount of rare but very high peaks in the signal. A reduced PAR allows for using a cheaper digital-to-analog converter and amplifier in the transmitter.Godkänd; 2000; 20070318 (ysko)
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Lopez, Jerry. "Optimal Dual Frames for Erasures and Discrete Gabor Frames." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4124.
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Since their discovery in the early 1950's, frames have emerged as an important tool in areas such as signal processing, image processing, data compression and sampling theory, just to name a few. Our purpose of this dissertation is to investigate dual frames and the ability to find dual frames which are optimal when coping with the problem of erasures in data transmission. In addition, we study a special class of frames which exhibit algebraic structure, discrete Gabor frames. Much work has been done in the study of discrete Gabor frames in Rn, but very little is known about the l2(Z) case or the l2(Zd) case. We establish some basic Gabor frame theory for l2(Z) and then generalize to the l2(Zd) case.Ph.D.
Department of Mathematics
Sciences
Mathematics PhD
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Miranda, Navarro Maria. "Comparative Study of Several Bases in Functional Analysis." Thesis, Linköpings universitet, Matematik och tillämpad matematik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150462.
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From the beginning of the study of spaces in functional analysis, bases have been an indispensable tool for operating with vectors and functions over a concrete space. Bases can be organized by types, depending on their properties. This thesis is intended to give an overview of some bases and their relations. We study Hamel basis, Schauder basis and Orthonormal basis; we give some properties and compare them in different spaces, explaining the results. For example, an infinite dimensional Hilbert space will never have a basis which is a Schauder basis and a Hamel basis at the same time, but if this space is separable it has an orthonormal basis, which is also a Schauder basis. The project deals mainly with Banach spaces, but we also talk about the case when the space is a pre Hilbert space.
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Chemistruck, Heather Michelle. "A Galerkin Approach to Define Measured Terrain Surfaces with Analytic Basis Vectors to Produce a Compact Representation." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/29585.
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The concept of simulation-based engineering has been embraced by virtually every research and industry sector (Sinha, Liang et al. 2001; Mocko and Fenves 2003). Engineering and science communities have become increasingly aware that computer simulation is an indispensable tool for resolving a multitude of scientific and technological problems. It is clearly desirable to gain a reliable perspective on the behaviour of a system early in the design stage, long before building costly prototypes (Chul and Ro 2002; Letherwood, Gunter et al. 2004; Makarand Datar 2007; Ersal, Fathy et al. 2008; Mueller, Ferris et al. 2009). Simulation tools have become a critical part of the automotive industry due to their ability to reduce the time and money spent in the development process.
Terrain is the principle source of vertical excitation to the vehicle and must be accurately represented in order to correctly predict the vehicle response in simulation. In this dissertation, non-deformable terrain surfaces are defined as a sequence of vectors, where each vector comprises terrain heights at locations oriented perpendicular to the direction of travel. The evolution and implications of terrain surface measurement techniques and existing methods for correcting INS drift are reviewed as a framework for a new compensation method for INS drift in terrain surface measurements. Each measurement is considered a combination of the true surface and the error surface, defined on a Hilbert vector space, in which the error is decomposed into drift (global error) and noise (local error). It is also desirable to develop a compact, path-specific, terrain surface representation that exploits the inherent anisotropicity in terrain over which vehicles traverse. In order to obtain this, a set of analytic basis vectors is formed from Gegenbauer polynomials, parameterized to approximate the empirical basis vectors of the true terrain surface. It is also desirable to evaluate vehicle models and tire models over a wide range of terrain types, but it is computationally impractical to store long distances of every terrain surface variation. This dissertation examines the terrain surface, rather than the terrain profile, to maximize the information available to the tire model (i.e. wheel path data). A method to decompose the terrain surface as a combination of deterministic and stochastic components is also developed.Ph. D.
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Nascimento, Carlos Alberto do. "Estudo sobre espaços de Banach e de Hilbert com aplicações em equações diferenciais, integrais e teoria da aproximação." Universidade Estadual Paulista (UNESP), 2018. http://hdl.handle.net/11449/154152.
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Neste trabalho, abordaremos os principais conceitos e propriedades sobre espaço de Banach e espaço de Hilbert com o objetivo de oferecer o conteúdo necessário para discutirmos algumas aplicações desses conceitos. Mostraremos a existência e unicidade de solução de Equações Diferenciais Ordinárias de Primeira Ordem, existência e unicidade de solução de certas Equações Integrais e existência e unicidade de melhor aproximação em espaços normados e de Hilbert.
In this work, we will discuss the main concepts and properties on Banach space and Hilbert space in order to offer the necessary content to discuss some applications of these concepts. We will show the existence and uniqueness of the solution of First Order Ordinary Differential Equations, existence and uniqueness of solution of certain Integral Equations and existence and uniqueness of better approximation in normed and Hilbert spaces.
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Kidzinski, Lukasz. "Inference for stationary functional time series: dimension reduction and regression." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209226.
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Les progrès continus dans les techniques du stockage et de la collection des données permettent d'observer et d'enregistrer des processus d’une façon presque continue. Des exemples incluent des données climatiques, des valeurs de transactions financières, des modèles des niveaux de pollution, etc. Pour analyser ces processus, nous avons besoin des outils statistiques appropriés. Une technique très connue est l'analyse de données fonctionnelles (ADF).L'objectif principal de ce projet de doctorat est d'analyser la dépendance temporelle de l’ADF. Cette dépendance se produit, par exemple, si les données sont constituées à partir d'un processus en temps continu qui a été découpé en segments, les jours par exemple. Nous sommes alors dans le cadre des séries temporelles fonctionnelles.
La première partie de la thèse concerne la régression linéaire fonctionnelle, une extension de la régression multivariée. Nous avons découvert une méthode, basé sur les données, pour choisir la dimension de l’estimateur. Contrairement aux résultats existants, cette méthode n’exige pas d'assomptions invérifiables.
Dans la deuxième partie, on analyse les modèles linéaires fonctionnels dynamiques (MLFD), afin d'étendre les modèles linéaires, déjà reconnu, dans un cadre de la dépendance temporelle. Nous obtenons des estimateurs et des tests statistiques par des méthodes d’analyse harmonique. Nous nous inspirons par des idées de Brillinger qui a étudié ces models dans un contexte d’espaces vectoriels.
Doctorat en Sciences
info:eu-repo/semantics/nonPublished
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Chakmak, Ryan. "Eigenvalues and Approximation Numbers." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2167.
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While the spectral theory of compact operators is known to many, knowledge regarding the relationship between eigenvalues and approximation numbers might be less known. By examining these numbers in tandem, one may develop a link between eigenvalues and l^p spaces. In this paper, we develop the background of this connection with in-depth examples.
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Shin, Hyejin. "Infinite dimensional discrimination and classification." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5832.
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Modern data collection methods are now frequently returning observations that should
be viewed as the result of digitized recording or sampling from stochastic processes rather
than vectors of finite length. In spite of great demands, only a few classification methodologies
for such data have been suggested and supporting theory is quite limited. The focus of
this dissertation is on discrimination and classification in this infinite dimensional setting.
The methodology and theory we develop are based on the abstract canonical correlation
concept of Eubank and Hsing (2005), and motivated by the fact that Fisher's discriminant
analysis method is intimately tied to canonical correlation analysis. Specifically, we have
developed a theoretical framework for discrimination and classification of sample paths
from stochastic processes through use of the Loeve-Parzen isomorphism that connects a
second order process to the reproducing kernel Hilbert space generated by its covariance
kernel. This approach provides a seamless transition between the finite and infinite dimensional
settings and lends itself well to computation via smoothing and regularization. In
addition, we have developed a new computational procedure and illustrated it with simulated
data and Canadian weather data.
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Abdellaoui, Taoufiq. "Distances de deux lois dans les espaces de Banach." Rouen, 1994. http://www.theses.fr/1994ROUE5003.
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La distance entre deux lois est étudiée lorsque les probabilités sont définies sur un espace de Banach séparable. Nous montrons que cette distance est atteinte par une fonction, dite associée, lorsque l'une des lois est diffuse l'autre discrète. Une condition nécessaire et suffisante pour reconnaitre le caractère associé est donnée par la cyclique monotonie. De plus un algorithme est donné pour obtenir de manière effective la fonction associée. Lorsque nous sommes dans un Hilbert séparable ces résultats sont étendus en utilisant des techniques de sous-gradients et d'analyse convexe
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Klepsch, Johannes [Verfasser], Claudia [Akademischer Betreuer] [Gutachter] Klüppelberg, Alexander [Gutachter] Aue, and Klaus [Gutachter] Mainzer. "Time series analysis in Hilbert spaces : Estimation of functional linear processes and prediction of traffic / Johannes Klepsch ; Gutachter: Alexander Aue, Klaus Mainzer, Claudia Klüppelberg ; Betreuer: Claudia Klüppelberg." München : Universitätsbibliothek der TU München, 2017. http://d-nb.info/1130323218/34.
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Torgovitski, Leonid [Verfasser], Josef G. [Gutachter] Steinebach, WOLFGANG [Gutachter] WEFELMEYER, and Piotr S. [Gutachter] Kokoszka. "Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence / Leonid Torgovitski ; Gutachter: Josef G. Steinebach, Wolfgang Wefelmeyer, Piotr S. Kokoszka." Köln : Universitäts- und Stadtbibliothek Köln, 2016. http://d-nb.info/1122262329/34.
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Ke, Chenlu. "A NEW INDEPENDENCE MEASURE AND ITS APPLICATIONS IN HIGH DIMENSIONAL DATA ANALYSIS." UKnowledge, 2019. https://uknowledge.uky.edu/statistics_etds/41.
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This dissertation has three consecutive topics. First, we propose a novel class of independence measures for testing independence between two random vectors based on the discrepancy between the conditional and the marginal characteristic functions. If one of the variables is categorical, our asymmetric index extends the typical ANOVA to a kernel ANOVA that can test a more general hypothesis of equal distributions among groups. The index is also applicable when both variables are continuous. Second, we develop a sufficient variable selection procedure based on the new measure in a large p small n setting. Our approach incorporates marginal information between each predictor and the response as well as joint information among predictors. As a result, our method is more capable of selecting all truly active variables than marginal selection methods. Furthermore, our procedure can handle both continuous and discrete responses with mixed-type predictors. We establish the sure screening property of the proposed approach under mild conditions. Third, we focus on a model-free sufficient dimension reduction approach using the new measure. Our method does not require strong assumptions on predictors and responses. An algorithm is developed to find dimension reduction directions using sequential quadratic programming. We illustrate the advantages of our new measure and its two applications in high dimensional data analysis by numerical studies across a variety of settings.
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Varagnolo, Damiano. "Distributed Parametric-Nonparametric Estimation in Networked Control Systems." Doctoral thesis, Università degli studi di Padova, 2011. http://hdl.handle.net/11577/3421610.
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In the framework of parametric and nonparametric distributed estimation, we introduce and mathematically analyze some consensus-based regression strategies characterized by a guess of the number of agents in the network as a parameter. The parametric estimators assume a-priori information about the finite set of parameters to be estimated, while the the nonparametric use a reproducing kernel Hilbert space as the hypothesis space. The analysis of the proposed distributed regressors offers some sufficient conditions assuring the estimators to perform better, under the variance of the estimation error metric, than local optimal ones. Moreover it characterizes, under euclidean distance metrics, the performance losses of the distributed estimators with respect to centralized optimal ones. We also offer a novel on-line algorithm that distributedly computes certificates of quality attesting the goodness of the estimation results, and show that the nonparametric distributed regressor is an approximate distributed Regularization Network requiring small computational, communication and data storage efforts. We then analyze the problem of estimating a function from different noisy data sets collected by spatially distributed sensors and subject to unknown temporal shifts, and perform time delay estimation through the minimization of functions of inner products in reproducing kernel Hilbert spaces.
Due to the importance of the knowledge of the number of agents in the previously analyzed algorithms, we also propose a design methodology for its distributed estimation. This algorithm is based on the following paradigm: some locally randomly generated values are exchanged among the various sensors, and are then modified by known consensus-based strategies. Statistical analysis of the a-consensus values allows the estimation of the number of sensors participating in the process. The first main feature of this approach is that algorithms are completely distributed, since they do not require leader election steps. Moreover sensors are not requested to transmit authenticating information like identification numbers or similar data, and thus the strategy can be implemented even if privacy problems arise. After a rigorous formulation of the paradigm we analyze some practical examples, fully characterize them from a statistical point of view, and finally provide some general theoretical results among with asymptotic analyses.In questa tesi vengono introdotti e analizzati alcuni algoritmi di regressione distribuita parametrica e nonparametrica, basati su tecniche di consenso e parametrizzati da un parametro il cui significato è una stima del numero di sensori presenti nella rete. Gli algoritmi parametrici assumono la conoscenza di informazione a-priori sulle quantità da stimare, mentre quelli nonparametrici utilizzano come spazio delle ipotesi uno spazio di Hilbert a nucleo riproducente. Dall'analisi degli stimatori distribuiti proposti si ricavano alcune condizioni sufficienti che, se assicurate, garantiscono che le prestazioni degli stimatori distribuiti sono migliori di quelli locali (usando come metrica la varianza dell'errore di stima). Inoltre dalla stessa analisi si caratterizzano le perdite di prestazioni che si hanno usando gli stimatori distribuiti invece che quelli centralizzati e ottimi (usando come metrica la distanza euclidea tra le due diverse stime ottenute). Inoltre viene offerto un nuovo algoritmo che calcola in maniera distribuita dei certificati di qualità che garantiscono la bontà dei risultati ottenuti con gli stimatori distribuiti. Si mostra inoltre come lo stimatore nonparametrico distribuito proposto sia in realtà una versione approssimata delle cosiddette ``Reti di Regolarizzazione'', e come esso richieda poche risorse computazionali, di memoria e di comunicazione tra sensori. Si analizza quindi il caso di sensori spazialmente distribuiti e soggetti a ritardi temporali sconosciuti. Si mostra dunque come si possano stimare, minimizzando opportune funzioni di prodotti interni negli spazi di Hilbert precedentemente considerati, sia la funzione vista dai sensori che i relativi ritardi visti da questi. A causa dell'importanza della conoscenza del numero di agenti negli algoritmi proposti precedentemente, viene proposta una nuova metodologia per sviluppare algoritmi di stima distribuita di tale numero, basata sulla seguente idea: come primo passo gli agenti generano localmente alcuni numeri, in maniera casuale e da una densità di probabilità nota a tutti. Quindi i sensori si scambiano e modificano questi dati usando algoritmi di consenso quali la media o il massimo; infine, tramite analisi statistiche sulla distribuzione finale dei dati modificati, si può ottenere dell'informazione su quanti agenti hanno partecipato al processo di consenso e modifica. Una caratteristica di questo approccio è che gli algoritmi sono completamente distribuiti, in quanto non richiedono passi di elezione di leaders. Un'altra è che ai sensori non è richiesto di trasmettere informazioni sensibili quali codici identificativi o altro, quindi la strategia è implementabile anche se in presenza di problemi di riservatezza. Dopo una formulazione rigorosa del paradigma, analizziamo alcuni esempi pratici, li caratterizziamo completamente dal punto di vista statistico, e infine offriamo alcuni risultati teorici generali e analisi asintotiche.
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Henchiri, Yousri. "L'approche Support Vector Machines (SVM) pour le traitement des données fonctionnelles." Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20187/document.
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L'Analyse des Données Fonctionnelles est un domaine important et dynamique en statistique. Elle offre des outils efficaces et propose de nouveaux développements méthodologiques et théoriques en présence de données de type fonctionnel (fonctions, courbes, surfaces, ...). Le travail exposé dans cette thèse apporte une nouvelle contribution aux thèmes de l'apprentissage statistique et des quantiles conditionnels lorsque les données sont assimilables à des fonctions. Une attention particulière a été réservée à l'utilisation de la technique Support Vector Machines (SVM). Cette technique fait intervenir la notion d'Espace de Hilbert à Noyau Reproduisant. Dans ce cadre, l'objectif principal est d'étendre cette technique non-paramétrique d'estimation aux modèles conditionnels où les données sont fonctionnelles. Nous avons étudié les aspects théoriques et le comportement pratique de la technique présentée et adaptée sur les modèles de régression suivants. Le premier modèle est le modèle fonctionnel de quantiles de régression quand la variable réponse est réelle, les variables explicatives sont à valeurs dans un espace fonctionnel de dimension infinie et les observations sont i.i.d.. Le deuxième modèle est le modèle additif fonctionnel de quantiles de régression où la variable d'intérêt réelle dépend d'un vecteur de variables explicatives fonctionnelles. Le dernier modèle est le modèle fonctionnel de quantiles de régression quand les observations sont dépendantes. Nous avons obtenu des résultats sur la consistance et les vitesses de convergence des estimateurs dans ces modèles. Des simulations ont été effectuées afin d'évaluer la performance des procédures d'inférence. Des applications sur des jeux de données réelles ont été considérées. Le bon comportement de l'estimateur SVM est ainsi mis en évidenceFunctional Data Analysis is an important and dynamic area of statistics. It offers effective new tools and proposes new methodological and theoretical developments in the presence of functional type data (functions, curves, surfaces, ...). The work outlined in this dissertation provides a new contribution to the themes of statistical learning and quantile regression when data can be considered as functions. Special attention is devoted to use the Support Vector Machines (SVM) technique, which involves the notion of a Reproducing Kernel Hilbert Space. In this context, the main goal is to extend this nonparametric estimation technique to conditional models that take into account functional data. We investigated the theoretical aspects and practical attitude of the proposed and adapted technique to the following regression models.The first model is the conditional quantile functional model when the covariate takes its values in a bounded subspace of the functional space of infinite dimension, the response variable takes its values in a compact of the real line, and the observations are i.i.d.. The second model is the functional additive quantile regression model where the response variable depends on a vector of functional covariates. The last model is the conditional quantile functional model in the dependent functional data case. We obtained the weak consistency and a convergence rate of these estimators. Simulation studies are performed to evaluate the performance of the inference procedures. Applications to chemometrics, environmental and climatic data analysis are considered. The good behavior of the SVM estimator is thus highlighted
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Schöckel, Thomas. "Aspekte unendlichdimensionaler Martingaltheorie und ihre Anwendung in der Theorie der Finanzmärkte." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2004. http://dx.doi.org/10.18452/15138.
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Wir modellieren einen Finanzmarkt mit unendlich vielen Wertpapieren als stochastischen Prozeß X in stetiger Zeit mit Werten in einem separablen Hilbertraum H. In diesem Rahmen zeigen wir die Äquivalenz von Vollständigkeit des Marktes und der Eindeutigkeit des äquivalenten Martingalmaßes unter der Bedingung, daß X stetige Pfade besitzt. Weiter zeigen wir, daß (unter gewissen technischen Bedingungen) für X die Abwesenheit von asymptotischer Arbitrage der ersten/zweiten Art (im Sinne von Kabanov/Kramkov) äquivalent zur Absolutstetigkeit des Referenzmaßes zu einem eindeutigen, lokal äquivalenten Martingalmaß ist. Hat X stetige Pfade, so ist die Abwesenheit von allgemeiner asymptotischer Arbitrage äquivalent zur Existenz eines äquivalenten lokalen Martingalmaßes. Außerdem geben wir ein Kriterium für die Existenz einer optionalen Zerlegung von X an. Dies wenden wir auf das Problem der Risikominimierung bei vorgegebener Investitionsobergrenze (effizientes Hedgen (Föllmer/Leukert)) an, um dieses im unendlichdimensionalen Kontext zu behandeln. Außerdem stellen wir eine unendlichdimensionale Erweiterung des Heath-Jarrow-Morton-Modells vor und nutzen den Potentialansatz nach Rodgers, um zwei weitere Zinsstrukturmodelle zu konstruieren. Als Beitrag zur allgemeinen stochastischen Analysis in Hilberträumen beweisen wir eine pfadweise Version der Itoformel für stochastische Prozesse mit stetigen Pfaden in einem separablen Hilbertraum. Daraus läßt sich eine pfadweise Version des Satzes über die Vertauschbarkeit von stochastischem und Lebesgue-Integral ableiten. Außerdem zeigen wir eine Version der Clark-Formel für eine Brownsche Bewegung mit Werten in einem Hilbertraum.We model a financial market with infinitely many assets as a stochastic process X with values in a separable Hilbert space H. In this setting we show the equivalence of market completeness and the uniqueness of the equivalent martingale measure, if X has continuous paths. Another result for our model is, that under some technical conditions, the absence of asymptotic arbitrage of the first/second kind (in the sense of Kabanov/Kramkov) is equivalent to the absolute continuity of the reference measure to a unique, locally equivalent, martingale measure. If X has continuous paths, the absence of general asymptotic arbitrage is equivalent to the existence of an equivalent local martingale measure. Furthermore, we give a sufficient condition for the existence of the optional decomposition of X. We apply this result to the problem of risk minimization with given upper limit for investion (efficient hedging (Föllmer/Leukert)). This allows us to solve this optimization problem in our infinite dimensional context. Another result is an infinite dimensional extension of the Heath-Jarrow-Morton term structure model. Two further term structure models are constructed, using the Markov potential approach developed by Rodgers. As a contribution to the theory of stochastic analysis in Hilbert spaces, we proof a pathwise version of the Ito formula for stochastic processes with continuous paths in a separable Hilbert space. This leads to a pathwise version of the interchangability theorem for stochastic and Lebesgue integrals. We also show a version of the Clark formula for Hilbert space valued Brownian motion.
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Saide, Chafic. "Filtrage adaptatif à l’aide de méthodes à noyau : application au contrôle d’un palier magnétique actif." Thesis, Troyes, 2013. http://www.theses.fr/2013TROY0018/document.
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L’estimation fonctionnelle basée sur les espaces de Hilbert à noyau reproduisant demeure un sujet de recherche actif pour l’identification des systèmes non linéaires. L'ordre du modèle croit avec le nombre de couples entrée-sortie, ce qui rend cette méthode inadéquate pour une identification en ligne. Le critère de cohérence est une méthode de parcimonie pour contrôler l’ordre du modèle. Le modèle est donc défini à partir d'un dictionnaire de faible taille qui est formé par les fonctions noyau les plus pertinentes.Une fonction noyau introduite dans le dictionnaire y demeure même si la non-stationnarité du système rend sa contribution faible dans l'estimation de la sortie courante. Il apparaît alors opportun d'adapter les éléments du dictionnaire pour réduire l'erreur quadratique instantanée et/ou mieux contrôler l'ordre du modèle.La première partie traite le sujet des algorithmes adaptatifs utilisant le critère de cohérence. L'adaptation des éléments du dictionnaire en utilisant une méthode de gradient stochastique est abordée pour deux familles de fonctions noyau. Cette partie a un autre objectif qui est la dérivation des algorithmes adaptatifs utilisant le critère de cohérence pour identifier des modèles à sorties multiples.La deuxième partie introduit d'une manière abrégée le palier magnétique actif (PMA). La proposition de contrôler un PMA par un algorithme adaptatif à noyau est présentée pour remplacer une méthode utilisant les réseaux de neurones à couches multiplesFunction approximation methods based on reproducing kernel Hilbert spaces are of great importance in kernel-based regression. However, the order of the model is equal to the number of observations, which makes this method inappropriate for online identification. To overcome this drawback, many sparsification methods have been proposed to control the order of the model. The coherence criterion is one of these sparsification methods. It has been shown possible to select a subset of the most relevant passed input vectors to form a dictionary to identify the model.A kernel function, once introduced into the dictionary, remains unchanged even if the non-stationarity of the system makes it less influent in estimating the output of the model. This observation leads to the idea of adapting the elements of the dictionary to obtain an improved one with an objective to minimize the resulting instantaneous mean square error and/or to control the order of the model.The first part deals with adaptive algorithms using the coherence criterion. The adaptation of the elements of the dictionary using a stochastic gradient method is presented for two types of kernel functions. Another topic is covered in this part which is the implementation of adaptive algorithms using the coherence criterion to identify Multiple-Outputs models.The second part introduces briefly the active magnetic bearing (AMB). A proposed method to control an AMB by an adaptive algorithm using kernel methods is presented to replace an existing method using neural networks
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Rossi, Dario. "Fracton phases: analytical description and simulations of their thermal behavior." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23919/.
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Many-body physics studies the collective behavior of systems with a large number of microscopic constituents. The interaction between the fundamental particles creates a common behavior within the system with emergent excitations exhibiting uncommon
characteristics. In three spatial dimensions it has recently been found that a new kind of particles can exist characterized by a fractionalized mobility, being either immobile or mobile only along sub-dimensional spaces: fractons.
In this thesis I explore fracton phases focusing on their topological and thermal properties. Fractons can be explained as a generalization of usual topological particles with some fundamental differences, which make fracton order a new field on its own. Fracton models are studied first from the point of view of exactly solvable lattice spin models, focusing on the similarities and differences with usual topological models. Fracton phases are also described through the use of symmetric tensor gauge theory. This gives a theoretical background which is used to explore some possible phases at finite densities of fractons, like Fermi liquids and quantum Hall states.
The thermal properties of such systems are studied in detail through the use of numerical simulations relying on exact-diagonalization. Various correspondences with systems featuring quantum many-body scars are found, in particular with the PXP model. The non-thermal behavior of the models under study is justified by the fragmentation of the Hilbert space in a large number of separated sub-sectors, not related to symmetries of the model. Further, the range of the local Hamiltonian operators is found to be of fundamental relevance in the thermal properties of the system. For certain ranges it is observed that the models are not able to reach the thermal state at long times. Instead, increasing the length of interactions the system becomes ergodic, with the exception of a small number of special eigenstates which remain non-thermal.
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Nikbakht, Silab Rasoul. "Unsupervised learning for parametric optimization in wireless networks." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671246.
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This thesis studies parametric optimization in cellular and cell-free networks, exploring data-based and expert-based paradigms. Power allocation and power control, which adjust the transmit power to meet different fairness criteria such as max-min or max-product, are crucial tasks in wireless communications that fall into the parametric optimization category. The state-of-the-art approaches for power control and power allocation often demand huge computational costs and are not suitable for real-time applications. To address this issue, we develop a general-purpose unsupervised-learning approach for solving parametric optimizations; and extend the well-known fractional power control algorithm.
In the data-based paradigm, we create an unsupervised learning framework that defines a custom neural network (NN), incorporating expert knowledge to the NN loss function to solve the power control and power allocation problems. In this approach, a feedforward NN is trained by repeatedly sampling the parameter space, but, rather than solving the associated optimization problem completely, a single step is taken along the gradient of the objective function. The resulting method is applicable for both convex and non-convex optimization problems. It offers two-to-three orders of magnitude speedup in the power control and power allocation problems compared to a convex solver—whenever appliable.
In the expert-driven paradigm, we investigate the extension of fractional power control to cell-free networks. The resulting closed-form solution can be evaluated for uplink and downlink effortlessly and reaches an (almost) optimum solution in the uplink case.
In both paradigms, we place a particular focus on large scale gains—the amount of attenuation experienced by the local-average received power. The slow-varying nature of the large-scale gains relaxes the need for a frequent update of the solutions in both the data-driven and expert-driven paradigms, enabling real-time application for both methods.Aqueta tesis estudia l’optimització paramètrica a les xarxes cel.lulars i xarxes cell-free, explotant els paradigmes basats en dades i basats en experts. L’assignació i control de la potencia, que ajusten la potencia de transmissió per complir amb diferents criteris d’equitat com max-min o max-product, son tasques crucials en les telecomunicacions inalàmbriques pertanyents a la categoria d’optimització paramètrica. Les tècniques d’última generació per al control i assignació de la potència solen exigir enormes costos computacionals i no son adequats per aplicacions en temps real. Per abordar aquesta qüestió, desenvolupem una tècnica de propòsit general utilitzant aprenentatge no supervisat per resoldre optimitzacions paramètriques; i al mateix temps ampliem el reconegut algoritme de control de potencia fraccionada. En el paradigma basat en dades, creem un marc d’aprenentatge no supervisat que defineix una xarxa neuronal (NN, sigles de Neural Network en Anglès) especifica, incorporant coneixements experts a la funció de cost de la NN per resoldre els problemes de control i assignació de potència. Dins d’aquest enfocament, s’entrena una NN de tipus feedforward mitjançant el mostreig repetit en l’espai de paràmetres, però, en lloc de resoldre completament el problema d’optimització associat, es pren un sol pas en la direcció del gradient de la funció objectiu. El mètode resultant ´es aplicable tant als problemes d’optimització convexos com no convexos. Això ofereix una acceleració de dos a tres ordres de magnitud en els problemes de control i assignació de potencia en comparació amb un algoritme de resolució convexa—sempre que sigui aplicable. En el paradigma dirigit per experts, investiguem l’extensió del control de potencia fraccionada a les xarxes sense cèl·lules. La solució tancada resultant pot ser avaluada per a l’enllaç de pujada i el de baixada sense esforç i assoleix una solució (gaire) òptima en el cas de l’enllaç de pujada. En ambdós paradigmes, ens centrem especialment en els guanys a gran escala—la quantitat d’atenuació que experimenta la potencia mitja local rebuda. La naturalesa de variació lenta dels guanys a gran escala relaxa la necessitat d’una actualització freqüent de les solucions tant en el paradigma basat en dades com en el basat en experts, permetent d’aquesta manera l’ús dels dos mètodes en aplicacions en temps real.
Esta tesis estudia la optimización paramétrica en las redes celulares y redes cell-free, explorando los paradigmas basados en datos y en expertos. La asignación y el control de la potencia, que ajustan la potencia de transmisión para cumplir con diferentes criterios de equidad como max-min o max-product, son tareas cruciales en las comunicaciones inalámbricas pertenecientes a la categoría de optimización paramétrica. Los enfoques más modernos de control y asignación de la potencia suelen exigir enormes costes computacionales y no son adecuados para aplicaciones en tiempo real. Para abordar esta cuestión, desarrollamos un enfoque de aprendizaje no supervisado de propósito general que resuelve las optimizaciones paramétricas y a su vez ampliamos el reconocido algoritmo de control de potencia fraccionada. En el paradigma basado en datos, creamos un marco de aprendizaje no supervisado que define una red neuronal (NN, por sus siglas en inglés) específica, incorporando conocimiento de expertos a la función de coste de la NN para resolver los problemas de control y asignación de potencia. Dentro de este enfoque, se entrena una NN de tipo feedforward mediante el muestreo repetido del espacio de parámetros, pero, en lugar de resolver completamente el problema de optimización asociado, se toma un solo paso en la dirección del gradiente de la función objetivo. El método resultante es aplicable tanto a los problemas de optimización convexos como no convexos. Ofrece una aceleración de dos a tres órdenes de magnitud en los problemas de control y asignación de potencia, en comparación con un algoritmo de resolución convexo—siempre que sea aplicable. Dentro del paradigma dirigido por expertos, investigamos la extensión del control de potencia fraccionada a las redes cell-free. La solución de forma cerrada resultante puede ser evaluada para el enlace uplink y el downlink sin esfuerzo y alcanza una solución (casi) óptima en el caso del enlace uplink. En ambos paradigmas, nos centramos especialmente en las large-scale gains— la cantidad de atenuación que experimenta la potencia media local recibida. La naturaleza lenta y variable de las ganancias a gran escala relaja la necesidad de una actualización frecuente de las soluciones tanto en el paradigma basado en datos como en el basado en expertos, permitiendo el uso de ambos métodos en aplicaciones en tiempo real.
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Basley, Jérémy. "An Experimental Investigation on Waves and Coherent Structures in a Three-Dimensional Open Cavity Flow." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112245/document.
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Une écoulement de cavité ouverte tridimensionnel saturé non-linéairement est étudié par une approche spatio-temporelle utilisant des données expérimentales résolues à la fois en temps et en espace. Ces données ont été acquises dans deux plans longitudinaux, respectivement perpendiculaire et parallèle au fond de la cavité, dans le régime incompressible, en air ou en eau. À l'aide de multiples méthodes de décompositions globales en temps et en espace, les ondes et les structures cohérentes constituant la dynamique dans le régime permanent et pouvant être produites par des mécanismes d'instabilités différents sont identifiées et caractérisées.Tout d'abord, on approfondit la compréhension de l'effet des non-linéarités sur les oscillations auto-entretenues de la couche cisaillée impactante et leurs interactions avec l'écoulement intra-cavitaire. En particulier, l'analyse spectrale d'une portion de l'espace des paramètres permet de mettre en évidence un lien entre l'accrochage des modes d'oscillations auto-entretenues, la modulation d'amplitude au niveau du coin impactant et l'intermittence de ces modes. De plus, l'observation des basses fréquences intéragissant fortement avec les oscillations de la couche de mélange démontre l'existence d'une dynamique tridimensionnelle intrinsèque à l'intérieur de la cavité malgré les perturbations causées par la couche cisaillée instable.Les analyses de stabilité linéaire ont montré que des instabilités centrifuges peuvent résulter de la courbure induite par la recirculation. L'étude de la dynamique après saturation révèle de nombreuses structures cohérentes dont les propriétés sont quantifiées et classées en s'appuyant sur la forme des instabilités sous-jacentes: des ondes transverses progressives ou stationnaires. Enfin, certains comportements des structures saturées suggèrent que les mécanismes non-linéaires gouvernant le développement de l'écoulement une fois sorti du régime linéaire pourraient être étudiés dans le cadre des équations d'amplitudeA space-time study of a three-dimensional nonlinearly saturated open cavity flow is undertaken using time-resolved space-extended experimental data, acquired in both cross-stream and spanwise planes, in incompressible air and water flows. Through use of multiple modal decompositions in time and space, the waves and coherent structures composing the dynamics in the permanent regime are identified and characterised with respect to the instabilities arising in the flow.Effects of nonlinearities are thoroughly investigated in the impinging shear layer, regarding the self-sustained oscillations and their interactions with the inner-flow. In particular, the analysis conducted throughout the parameter space enlightens a global connection between the selection of locked-on modes and the amplitude modulation at the impingement and the mode switching phenomenon. Furthermore, observations of low frequencies interacting drastically with the shear layer flapping motion underline the existence of intrinsic coherent three-dimensional dynamics inside the cavity in spite of the shear layer disturbances.Linear stability analyses have demonstrated that centrifugal instabilities are at play along the main recirculation. The present investigation of the dynamics after onset of the saturation reveals numerous space-time coherent structures, whose properties are quantified and classified with respect to the underlying instabilities: travelling or standing spanwise waves. Finally, some patterns exhibited by the saturated structures suggest that the nonlinear mechanisms governing the mutations of the flow after the linear regime could gain more insight in the frame of amplitude equations
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Bhattacharjee, Monojit. "Analytic Models, Dilations, Wandering Subspaces and Inner Functions." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4241.
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This thesis concerns dilation theory, analytic models, joint invariant subspaces, reproducing kernelHilbert spaces and multipliers associated to commuting tuples of bounded linear operators on Hilbert spaces. The main contribution of this thesis is twofold: dilation and analytic model theory for n-tuples of (1) commuting contractions (in the setting of the unit polydisc), and (2) commuting row contractions (in the setting of the unit ball). On n-tuples of commuting contractions: We study analytic models of operators with some positivity assumptions and quotient modules of function Hilbert spaces over polydisc. We prove that for an m-hypercontraction T 2 C¢0 on a Hilbert space H, there exist Hilbert spaces E and E¤, and a partially isometric multiplier µ 2M ¡H2 E (D), A2 m(E¤) ¢ such that H » Æ Qµ Æ A2 m(E¤)ªµH2 E (D), and T » Æ PQµMz jQµ , where A2 m(E¤) is the E¤-valued weighted Bergman space and H2
E (D) is the E -valued Hardy space over the unit disc D.
We then proceed to study and develop analytic models for doubly commuting n-tuples of operators and investigate their applications to joint shift co-invariant subspaces of reproducing kernel Hilbert spaces over polydisc. In particular, we completely analyze doubly commuting quotient modules of a large class of reproducing kernel Hilbert modules, in the sense of Arazy and Englis, over the unit polydisc Dn. On commuting row contractions: We study wandering subspaces for commuting tuples of bounded operators on Hilbert spaces. We prove that for a large class of analytic functional Hilbert spaces HK on the unit ball in Cn, wandering subspaces for restrictions of the multiplication tupleMz Æ (Mz1 , . . . ,Mzn ) can be described in terms of suitable HK -inner functions. We prove that, HK -inner functions are contractive multipliers and deduce a result on the multiplier norm of quasi-homogenous polynomials as an application. Along the way we prove a refinement of a result of Arveson on the uniqueness of minimal dilations of pure row contractions.
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Chandel, Vikramjeet Singh. "The Pick-Nevanlinna Interpolation Problem : Complex-analytic Methods in Special Domains." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/3700.
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The Pick–Nevanlinna interpolation problem, in its fullest generality, is as follows:
Given domains D1, D2 in complex Euclidean spaces, and a set f¹ zi; wiº : 1 i N g D1 D2, where zi are distinct and N 2 š+, N 2, find necessary and sufficient conditions for the existence of a holomorphic map F : D1 ! D2 such that F¹ziº = wi, 1 i N.
When such a map F exists, we say that F is an interpolant of the data. Of course, this problem is intractable at the above level of generality. However, two special cases of the problem — which we shall study in this thesis — have been of lasting interest:
Interpolation from the polydisc to the unit disc. This is the case D1 = „n and D2 = „, where „ denotes the open unit disc in the complex plane and n 2 š+. The problem itself originates with Georg Pick’s well-known theorem (independently discovered by Nevanlinna) for the case n = 1. Much later, Sarason gave another proof of Pick’s result using an operator-theoretic approach, which is very influential. Using this approach for n 2, Agler–McCarthy provided a solution to the problem with the restriction that the interpolant is in the Schur– Agler class. This is notable because, when n = 2, the latter result completely solves the problem for the case D1 = „2; D2 = „. However, Pick’s approach can also be effective for n 2. In this thesis, we give an alternative characterization for the existence of a 3-point interpolant based on Pick’s approach and involving the study of rational inner functions.
Cole–Lewis–Wermer lifted Sarason’s approach to uniform algebras — leading to a char-acterization for the existence of an interpolant in terms of the positivity of a large, rather abstractly-defined family of N N matrices. McCullough later refined their result by identifying a smaller family of matrices. The second result of this thesis is in the same vein, namely: it provides a characterization of those data that admit a „n-to-„ interpolant in terms of the positivity of a family of N N matrices parametrized by a class of polynomials.
Interpolation from the unit disc to the spectral unit ball. This is the case D1 = „ and D2 = n , where n denotes the set of all n n matrices with spectral radius less than 1. The interest in this arises from problems in Control Theory. Bercovici–Foias–Tannenbaum adapted Sarason’s methods to give a (somewhat hard-to-check) characterization for the existence of an interpolant under a very mild restriction. Later, Agler–Young established a relation between the interpolation problem in the spectral unit ball and that in the symmetrized polydisc — leading to a necessary condition for the existence of an interpolant. Bharali later provided a new inequivalent necessary condition for the existence of an interpolant for any n and N = 2. In this thesis, we shall present a necessary condition for the existence of an interpolant in the case when N = 3. This we shall achieve by adapting Pick’s approach and applying the aforementioned result of Bharali.
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Chandel, Vikramjeet Singh. "The Pick-Nevanlinna Interpolation Problem : Complex-analytic Methods in Special Domains." Thesis, 2017. http://etd.iisc.ernet.in/2005/3700.
Full textAbstract:
The Pick–Nevanlinna interpolation problem, in its fullest generality, is as follows:
Given domains D1, D2 in complex Euclidean spaces, and a set f¹ zi; wiº : 1 i N g D1 D2, where zi are distinct and N 2 š+, N 2, find necessary and sufficient conditions for the existence of a holomorphic map F : D1 ! D2 such that F¹ziº = wi, 1 i N.
When such a map F exists, we say that F is an interpolant of the data. Of course, this problem is intractable at the above level of generality. However, two special cases of the problem — which we shall study in this thesis — have been of lasting interest:
Interpolation from the polydisc to the unit disc. This is the case D1 = „n and D2 = „, where „ denotes the open unit disc in the complex plane and n 2 š+. The problem itself originates with Georg Pick’s well-known theorem (independently discovered by Nevanlinna) for the case n = 1. Much later, Sarason gave another proof of Pick’s result using an operator-theoretic approach, which is very influential. Using this approach for n 2, Agler–McCarthy provided a solution to the problem with the restriction that the interpolant is in the Schur– Agler class. This is notable because, when n = 2, the latter result completely solves the problem for the case D1 = „2; D2 = „. However, Pick’s approach can also be effective for n 2. In this thesis, we give an alternative characterization for the existence of a 3-point interpolant based on Pick’s approach and involving the study of rational inner functions.
Cole–Lewis–Wermer lifted Sarason’s approach to uniform algebras — leading to a char-acterization for the existence of an interpolant in terms of the positivity of a large, rather abstractly-defined family of N N matrices. McCullough later refined their result by identifying a smaller family of matrices. The second result of this thesis is in the same vein, namely: it provides a characterization of those data that admit a „n-to-„ interpolant in terms of the positivity of a family of N N matrices parametrized by a class of polynomials.
Interpolation from the unit disc to the spectral unit ball. This is the case D1 = „ and D2 = n , where n denotes the set of all n n matrices with spectral radius less than 1. The interest in this arises from problems in Control Theory. Bercovici–Foias–Tannenbaum adapted Sarason’s methods to give a (somewhat hard-to-check) characterization for the existence of an interpolant under a very mild restriction. Later, Agler–Young established a relation between the interpolation problem in the spectral unit ball and that in the symmetrized polydisc — leading to a necessary condition for the existence of an interpolant. Bharali later provided a new inequivalent necessary condition for the existence of an interpolant for any n and N = 2. In this thesis, we shall present a necessary condition for the existence of an interpolant in the case when N = 3. This we shall achieve by adapting Pick’s approach and applying the aforementioned result of Bharali.
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Sorensen, Julian Karl. "White noise analysis and stochastic evolution equations / Julian Sorensen." Thesis, 2001. http://hdl.handle.net/2440/19834.
Full text
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Turner, Matthew D. "Explicit Lp-norm estimates of infinitely divisible random vectors in Hilbert spaces with applications." 2011. http://trace.tennessee.edu/utk_graddiss/1035.
Full textAbstract:
I give explicit estimates of the Lp-norm of a mean zero infinitely divisible random vector taking values in a Hilbert space in terms of a certain mixture of the L2- and Lp-norms of the Levy measure. Using decoupling inequalities, the stochastic integral driven by an infinitely divisible random measure is defined. As a first application utilizing the Lp-norm estimates, computation of Ito Isomorphisms for different types of stochastic integrals are given. As a second application, I consider the discrete time signal-observation model in the presence of an alpha-stable noise environment. Formulation is given to compute the optimal linear estimate of the system state.
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王逢盛. "Approximation methods in a Hilbert space for heat transfer, system analysis and optimal control." Thesis, 1986. http://ndltd.ncl.edu.tw/handle/66047063856174145052.
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Carter, James Michael. "Commutants of composition operators on the Hardy space of the disk." 2013. http://hdl.handle.net/1805/3659.
Full textAbstract:
Indiana University-Purdue University Indianapolis (IUPUI)The main part of this thesis, Chapter 4, contains results on the commutant of a semigroup of operators defined on the Hardy Space of the disk where the operators have hyperbolic non-automorphic symbols. In particular, we show in Chapter 5 that the commutant of the semigroup of operators is in one-to-one correspondence with a Banach algebra of bounded analytic functions on an open half-plane. This algebra of functions is a subalgebra of the standard Newton space. Chapter 4 extends previous work done on maps with interior fixed point to the case of the symbol of the composition operator having a boundary fixed point.
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Thompson, Derek Allen. "Restrictions to Invariant Subspaces of Composition Operators on the Hardy Space of the Disk." 2014. http://hdl.handle.net/1805/3881.
Full textAbstract:
Indiana University-Purdue University Indianapolis (IUPUI)Invariant subspaces are a natural topic in linear algebra and operator theory. In some rare cases, the restrictions of operators to different invariant subspaces are unitarily equivalent, such as certain restrictions of the unilateral shift on the Hardy space of the disk. A composition operator with symbol fixing 0 has a nested sequence of invariant subspaces, and if the symbol is linear fractional and extremally noncompact, the restrictions to these subspaces all have the same norm and spectrum. Despite this evidence, we will use semigroup techniques to show many cases where the restrictions are still not unitarily equivalent.
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Martin, Robert. "Bandlimited functions, curved manifolds, and self-adjoint extensions of symmetric operators." Thesis, 2008. http://hdl.handle.net/10012/3698.
Full textAbstract:
Sampling theory is an active field of research that spans a variety of disciplines from communication engineering to pure mathematics. Sampling theory provides the crucial connection between continuous and discrete representations of information that enables one store continuous signals as discrete, digital data with minimal error. It is this connection that allows communication engineers to realize many of our modern digital technologies including cell phones and compact disc players.
This thesis focuses on certain non-Fourier generalizations of sampling theory and their applications. In particular, non-Fourier analogues of bandlimited functions and extensions of sampling theory to functions on curved manifolds are studied. New results in bandlimited function theory, sampling theory on curved manifolds, and the theory of self-adjoint extensions of symmetric operators are presented. Besides being of mathematical interest in itself, the research contained in this thesis has applications to quantum physics on curved space and could potentially lead to more efficient information storage methods in communication engineering.
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Pal, Sourav. "Dilations, Functoinal Model And A Complete Unitary Invariant Of A r-contraction." Thesis, 2011. https://etd.iisc.ac.in/handle/2005/2182.
Full textAbstract:
A pair of commuting bounded operators (S, P) for which the set
r = {(z 1 +z 2,z 1z 2) : |z 1| ≤1, |z 2| ≤1} C2 is a spectral set, is called a r-contraction in the literature. For a contraction P and a bounded commutant S of P, we seek a solution of the operator equation
S –S*P = (I –P*P)½ X(I –P*P)½
where X is a bounded operator on Ran(I – P*P)½ with numerical radius of X being not
greater than 1. We show the existence and uniqueness of solution to the operator equation above when (S,P) is a r-contraction. We call the unique solution, the fundamental operator of the r-contraction (S,P). As the title indicates, there are three parts of this thesis and the main role in all three parts is played by the fundamental operator. The existence of the fundamental operator allows us to explicitly construct a r-isometric dilation of a r-contraction (S,P), whereas its uniqueness guarantees the uniqueness of the minimal r-isometric dilation. The fundamental operator helps us to produce a genuine functional model for pure r-contractions. Also it leads us to a complete unitary invariant for pure r-contractions. We decipher the structures of r-isometries and r-unitaries by characterizing them in several different ways. We establish the fact that for every pure r-contraction (S,P), there is a bounded operator C with numerical radius being not greater than 1 such that S = C + C* P. When (S,P) is a r-isometry, S has the same form where P is an isometry commuting with C and C*. Also when (S,P) is a r-unitary, S has the same form too with P and C being commuting unitaries. Examples of r-contractions on reproducing kernel Hilbert spaces and their dilations are discussed.
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Pal, Sourav. "Dilations, Functoinal Model And A Complete Unitary Invariant Of A r-contraction." Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2182.
Full textAbstract:
A pair of commuting bounded operators (S, P) for which the set
r = {(z 1 +z 2,z 1z 2) : |z 1| ≤1, |z 2| ≤1} C2 is a spectral set, is called a r-contraction in the literature. For a contraction P and a bounded commutant S of P, we seek a solution of the operator equation
S –S*P = (I –P*P)½ X(I –P*P)½
where X is a bounded operator on Ran(I – P*P)½ with numerical radius of X being not
greater than 1. We show the existence and uniqueness of solution to the operator equation above when (S,P) is a r-contraction. We call the unique solution, the fundamental operator of the r-contraction (S,P). As the title indicates, there are three parts of this thesis and the main role in all three parts is played by the fundamental operator. The existence of the fundamental operator allows us to explicitly construct a r-isometric dilation of a r-contraction (S,P), whereas its uniqueness guarantees the uniqueness of the minimal r-isometric dilation. The fundamental operator helps us to produce a genuine functional model for pure r-contractions. Also it leads us to a complete unitary invariant for pure r-contractions. We decipher the structures of r-isometries and r-unitaries by characterizing them in several different ways. We establish the fact that for every pure r-contraction (S,P), there is a bounded operator C with numerical radius being not greater than 1 such that S = C + C* P. When (S,P) is a r-isometry, S has the same form where P is an isometry commuting with C and C*. Also when (S,P) is a r-unitary, S has the same form too with P and C being commuting unitaries. Examples of r-contractions on reproducing kernel Hilbert spaces and their dilations are discussed.
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Rieger, Christian. "Sampling Inequalities and Applications." Doctoral thesis, 2008. http://hdl.handle.net/11858/00-1735-0000-0006-B3B9-0.
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Hoang, Thai Duy. "Fourier and Variational Based Approaches for Fingerprint Segmentation." Doctoral thesis, 2015. http://hdl.handle.net/11858/00-1735-0000-0022-5FEF-2.
Full text
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Suresh, V. "Image Structures For Steganalysis And Encryption." Thesis, 2010. https://etd.iisc.ac.in/handle/2005/2273.
Full textAbstract:
In this work we study two aspects of image security: improper usage and illegal access of images. In the first part we present our results on steganalysis – protection against improper usage of images. In the second part we present our results on image encryption – protection against illegal access of images.
Steganography is the collective name for methodologies that allow the creation of invisible –hence secret– channels for information transfer. Steganalysis, the counter to steganography, is a collection of approaches that attempt to detect and quantify the presence of hidden messages in cover media.
First we present our studies on stego-images using features developed for data stream classification towards making some qualitative assessments about the effect of steganography on the lower order bit planes(LSB) of images. These features are effective in classifying different data streams. Using these features, we study the randomness properties of image and stego-image LSB streams and observe that data stream analysis techniques are inadequate for steganalysis purposes. This provides motivation to arrive at steganalytic techniques that go beyond the LSB properties. We then present our steganalytic approach which takes into account such properties.
In one such approach, we perform steganalysis from the point of view of quantifying the effect of perturbations caused by mild image processing operations–zoom-in/out, rotation, distortions–on stego-images. We show that this approach works both in detecting and estimating the presence of stego-contents for a particularly difficult steganographic technique known as LSB matching steganography.
Next, we present our results on our image encryption techniques. Encryption approaches which are used in the context of text data are usually unsuited for the purposes of encrypting images(and multimedia objects) in general. The reasons are: unlike text, the volume to be encrypted could be huge for images and leads to increased computational requirements; encryption used for text renders images incompressible thereby resulting in poor use of bandwidth. These issues are overcome by designing image encryption approaches that obfuscate the image by intelligently re-ordering the pixels or encrypt only parts of a given image in attempts to render them imperceptible. The obfuscated image or the partially encrypted image is still amenable to compression. Efficient image encryption schemes ensure that the obfuscation is not compromised by the inherent correlations present in the image. Also they ensure that the unencrypted portions of the image do not provide information about the encrypted parts. In this work we present two approaches for efficient image encryption.
First, we utilize the correlation preserving properties of the Hilbert space-filling-curves to reorder images in such a way that the image is obfuscated perceptually. This process does not compromise on the compressibility of the output image. We show experimentally that our approach leads to both perceptual security and perceptual encryption. We then show that the space-filling curve based approach also leads to more efficient partial encryption of images wherein only the salient parts of the image are encrypted thereby reducing the encryption load.
In our second approach, we show that Singular Value Decomposition(SVD) of images is useful from the point of image encryption by way of mismatching the unitary matrices resulting from the decomposition of images. It is seen that the images that result due to the mismatching operations are perceptually secure.
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Suresh, V. "Image Structures For Steganalysis And Encryption." Thesis, 2010. http://etd.iisc.ernet.in/handle/2005/2273.
Full textAbstract:
In this work we study two aspects of image security: improper usage and illegal access of images. In the first part we present our results on steganalysis – protection against improper usage of images. In the second part we present our results on image encryption – protection against illegal access of images.
Steganography is the collective name for methodologies that allow the creation of invisible –hence secret– channels for information transfer. Steganalysis, the counter to steganography, is a collection of approaches that attempt to detect and quantify the presence of hidden messages in cover media.
First we present our studies on stego-images using features developed for data stream classification towards making some qualitative assessments about the effect of steganography on the lower order bit planes(LSB) of images. These features are effective in classifying different data streams. Using these features, we study the randomness properties of image and stego-image LSB streams and observe that data stream analysis techniques are inadequate for steganalysis purposes. This provides motivation to arrive at steganalytic techniques that go beyond the LSB properties. We then present our steganalytic approach which takes into account such properties.
In one such approach, we perform steganalysis from the point of view of quantifying the effect of perturbations caused by mild image processing operations–zoom-in/out, rotation, distortions–on stego-images. We show that this approach works both in detecting and estimating the presence of stego-contents for a particularly difficult steganographic technique known as LSB matching steganography.
Next, we present our results on our image encryption techniques. Encryption approaches which are used in the context of text data are usually unsuited for the purposes of encrypting images(and multimedia objects) in general. The reasons are: unlike text, the volume to be encrypted could be huge for images and leads to increased computational requirements; encryption used for text renders images incompressible thereby resulting in poor use of bandwidth. These issues are overcome by designing image encryption approaches that obfuscate the image by intelligently re-ordering the pixels or encrypt only parts of a given image in attempts to render them imperceptible. The obfuscated image or the partially encrypted image is still amenable to compression. Efficient image encryption schemes ensure that the obfuscation is not compromised by the inherent correlations present in the image. Also they ensure that the unencrypted portions of the image do not provide information about the encrypted parts. In this work we present two approaches for efficient image encryption.
First, we utilize the correlation preserving properties of the Hilbert space-filling-curves to reorder images in such a way that the image is obfuscated perceptually. This process does not compromise on the compressibility of the output image. We show experimentally that our approach leads to both perceptual security and perceptual encryption. We then show that the space-filling curve based approach also leads to more efficient partial encryption of images wherein only the salient parts of the image are encrypted thereby reducing the encryption load.
In our second approach, we show that Singular Value Decomposition(SVD) of images is useful from the point of image encryption by way of mismatching the unitary matrices resulting from the decomposition of images. It is seen that the images that result due to the mismatching operations are perceptually secure.