Relevant bibliographies by topics / Inverse problems

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Inverse problems'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 June 2025

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Journal articles on the topic "Inverse problems"

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Coleman, Rodney. "Inverse problems." Journal of Microscopy 153, no. 3 (1989): 233–48. http://dx.doi.org/10.1111/j.1365-2818.1989.tb01475.x.

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Tanaka, Masa, and A. Kassab. "Inverse problems." Engineering Analysis with Boundary Elements 28, no. 3 (2004): 181. http://dx.doi.org/10.1016/s0955-7997(03)00048-1.

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Bunge, Mario. "Inverse Problems." Foundations of Science 24, no. 3 (2019): 483–525. http://dx.doi.org/10.1007/s10699-018-09577-1.

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Romanov, V. G. "SOME GEOMETRIC ASPECTS IN INVERSE PROBLEMS." Eurasian Journal of Mathematical and Computer Applications 3, no. 1 (2015): 68–84. http://dx.doi.org/10.32523/2306-3172-2015-3-4-68-84.

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Kabanikhin, S. I., O. I. Krivorotko, D. V. Ermolenko, V. N. Kashtanova, and V. A. Latyshenko. "INVERSE PROBLEMS OF IMMUNOLOGY AND EPIDEMIOLOGY." Eurasian Journal of Mathematical and Computer Applications 5, no. 2 (2017): 14–35. http://dx.doi.org/10.32523/2306-3172-2017-5-2-14-35.

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Iwamoto, Seiichi, and Takayuki Ueno. "INVERSE PARTITION PROBLEMS." Bulletin of informatics and cybernetics 31, no. 1 (1999): 67–90. http://dx.doi.org/10.5109/13481.

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Chu, Moody T. "Inverse Eigenvalue Problems." SIAM Review 40, no. 1 (1998): 1–39. http://dx.doi.org/10.1137/s0036144596303984.

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Greensite, Fred. "Partial inverse problems." Inverse Problems 22, no. 2 (2006): 461–79. http://dx.doi.org/10.1088/0266-5611/22/2/005.

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Isakov, Victor. "Inverse obstacle problems." Inverse Problems 25, no. 12 (2009): 123002. http://dx.doi.org/10.1088/0266-5611/25/12/123002.

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Horváth, Miklós, and Orsolya Sáfár. "Inverse eigenvalue problems." Journal of Mathematical Physics 57, no. 11 (2016): 112102. http://dx.doi.org/10.1063/1.4964390.

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Dissertations / Theses on the topic "Inverse problems"

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Chen, Xudong 1977. "Inverse problems in electromagnetics." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33933.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Vita.<br>Includes bibliographical references (p. 155-164).<br>Two inverse problems in electromagnetics are investigated in this thesis. The first is the retrieval of the effective constitutive parameters of metamaterials from the measurement of the reflection and the transmission coefficients. A robust method is proposed for the retrieval of metamaterials as isotropic media, and four improvements over the existing methods make the retrieval results more stable. Next, a new scheme is presented for the retrieval of a specific bianisotropic metamaterial that consists of split-ring resonators, which signifies that the cross polarization terms of the metamaterial are quantitatively investigated for the first time. Finally, an optimization approach is designed to achieve the retrieval of general bianisotropic media with 72 unknown parameters. The hybrid algorithm combining the differential evolution (DE) algorithm and the simplex method steadily converges to the exact solution. The second inverse problem deals with the detection and the classification of buried metallic objects using electromagnetic induction (EMI). Both the exciting and the induced magnetic fields are expanded as a linear combination of basic modes in the spheroidal coordinate system. Due to the orthogonality and the completeness of the spheroidal basic modes, the scattering coefficients are uniquely determined and are characteristics of the object.<br>(cont.) The scattering coefficients are retrieved from the knowledge of the induced fields, where both synthetic and measurement data are used. The ill-conditioning issue is dealt with by mode truncation and Tikhonov regularization technique. Stored in a library, the scattering coefficients can produce fast forward models for use in pattern matching. In addition, they can be used to train support vector machine (SVM) to sort objects into generic classes.<br>by Xudong Chen.<br>Ph.D.
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Deolmi, Giulia. "Computational Parabolic Inverse Problems." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3423351.

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This thesis presents a general approach to solve numerically parabolic Inverse Problems, whose underlying mathematical model is discretized using the Finite Element method. The proposed solution is based upon an adaptive parametrization and it is applied specically to a geometric conduction inverse problem of corrosion estimation and to a boundary convection inverse problem of pollution rate estimation.<br>In questa tesi viene presentato un approccio numerico volto alla risoluzione di problemi inversi parabolici, basato sull'utilizzo di una parametrizzazione adattativa. L'algoritmo risolutivo viene descritto per due specici problemi: mentre il primo consiste nella stima della corrosione di una faccia incognita del dominio, il secondo ha come scopo la quanticazione di inquinante immesso in un fiume.
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Debarnot, Valentin. "Microscopie computationnelle." Thesis, Toulouse 3, 2020. http://www.theses.fr/2020TOU30156.

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Les travaux présentés de cette thèse visent à proposer des outils numériques et théoriques pour la résolution de problèmes inverses en imagerie. Nous nous intéressons particulièrement au cas où l'opérateur d'observation (e.g. flou) n'est pas connu. Les résultats principaux de cette thèse s'articulent autour de l'estimation et l'identification de cet opérateur d'observation. Une approche plébiscitée pour estimer un opérateur de dégradation consiste à observer un échantillon contenant des sources ponctuelles (microbilles en microscopie, étoiles en astronomie). Une telle acquisition fournit une mesure de la réponse impulsionnelle de l'opérateur en plusieurs points du champ de vue. Le traitement de cette observation requiert des outils robustes pouvant utiliser rapidement les données rencontrées en pratique. Nous proposons une boîte à outils qui estime un opérateur de dégradation à partir d'une image contenant des sources ponctuelles. L'opérateur estimé à la propriété qu'en tout point du champ de vue, sa réponse impulsionnelle s'exprime comme une combinaison linéaire de fonctions élémentaires. Cela permet d'estimer des opérateurs invariants (convolutions) et variants (développement en convolution-produit) spatialement. Une spécificité importante de cette boîte à outils est son caractère automatique : seul un nombre réduit de paramètres facilement accessibles permettent de couvrir une grande majorité des cas pratiques. La taille de la source ponctuelle (e.g. bille), le fond et le bruit sont également pris en compte dans l'estimation. Cet outil se présente sous la forme d'un module appelé PSF-Estimator pour le logiciel Fiji, et repose sur une implémentation parallélisée en C++. En réalité, les opérateurs modélisant un système optique varient d'une expérience à une autre, ce qui, dans l'idéal, nécessite une calibration du système avant chaque acquisition. Pour pallier à cela, nous proposons de représenter un système optique non pas par un unique opérateur de dégradation, mais par un sous-espace d'opérateurs. Cet ensemble doit permettre de représenter chaque opérateur généré par un microscope. Nous introduisons une méthode d'estimation d'un tel sous-espace à partir d'une collection d'opérateurs de faible rang (comme ceux estimés par la boîte à outils PSF-Estimator). Nous montrons que sous des hypothèses raisonnables, ce sous-espace est de faible dimension et est constitué d'éléments de faible rang. Dans un second temps, nous appliquons ce procédé en microscopie sur de grands champs de vue et avec des opérateurs variant spatialement. Cette mise en œuvre est possible grâce à l'utilisation de méthodes complémentaires pour traiter des images réelles (e.g. le fond, le bruit, la discrétisation de l'observation). La construction d'un sous-espace d'opérateurs n'est qu'une étape dans l'étalonnage de systèmes optiques et la résolution de problèmes inverses. [...]<br>The contributions of this thesis are numerical and theoretical tools for the resolution of blind inverse problems in imaging. We first focus in the case where the observation operator is unknown (e.g. microscopy, astronomy, photography). A very popular approach consists in estimating this operator from an image containing point sources (microbeads or fluorescent proteins in microscopy, stars in astronomy). Such an observation provides a measure of the impulse response of the degradation operator at several points in the field of view. Processing this observation requires robust tools that can rapidly use the data. We propose a toolbox that estimates a degradation operator from an image containing point sources. The estimated operator has the property that at any location in the field of view, its impulse response is expressed as a linear combination of elementary estimated functions. This makes it possible to estimate spatially invariant (convolution) and variant (product-convolution expansion) operators. An important specificity of this toolbox is its high level of automation: only a small number of easily accessible parameters allows to cover a large majority of practical cases. The size of the point source (e.g. bead), the background and the noise are also taken in consideration in the estimation. This tool, coined PSF-estimator, comes in the form of a module for the Fiji software, and is based on a parallelized implementation in C++. The operators generated by an optical system are usually changing for each experiment, which ideally requires a calibration of the system before each acquisition. To overcome this, we propose to represent an optical system not by a single operator (e.g. convolution blur with a fixed kernel for different experiments), but by subspace of operators. This set allows to represent all the possible states of a microscope. We introduce a method for estimating such a subspace from a collection of low rank operators (such as those estimated by the toolbox PSF-Estimator). We show that under reasonable assumptions, this subspace is low-dimensional and consists of low rank elements. In a second step, we apply this process in microscopy on large fields of view and with spatially varying operators. This implementation is possible thanks to the use of additional methods to process real images (e.g. background, noise, discretization of the observation).The construction of an operator subspace is only one step in the resolution of blind inverse problems. It is then necessary to identify the degradation operator in this set from a single observed image. In this thesis, we provide a mathematical framework to this operator identification problem in the case where the original image is constituted of point sources. Theoretical conditions arise from this work, allowing a better understanding of the conditions under which this problem can be solved. We illustrate how this formal study allows the resolution of a blind deblurring problem on a microscopy example.[...]
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Kitic, Srdan. "Cosparse regularization of physics-driven inverse problems." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S152/document.

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Les problèmes inverses liés à des processus physiques sont d'une grande importance dans la plupart des domaines liés au traitement du signal, tels que la tomographie, l'acoustique, les communications sans fil, le radar, l'imagerie médicale, pour n'en nommer que quelques uns. Dans le même temps, beaucoup de ces problèmes soulèvent des défis en raison de leur nature mal posée. Par ailleurs, les signaux émanant de phénomènes physiques sont souvent gouvernées par des lois s'exprimant sous la forme d'équations aux dérivées partielles (EDP) linéaires, ou, de manière équivalente, par des équations intégrales et leurs fonctions de Green associées. De plus, ces phénomènes sont habituellement induits par des singularités, apparaissant comme des sources ou des puits d'un champ vectoriel. Dans cette thèse, nous étudions en premier lieu le couplage entre de telles lois physiques et une hypothèse initiale de parcimonie des origines du phénomène physique. Ceci donne naissance à un concept de dualité des régularisations, formulées soit comme un problème d'analyse coparcimonieuse (menant à la représentation en EDP), soit comme une parcimonie à la synthèse équivalente à la précédente (lorsqu'on fait plutôt usage des fonctions de Green). Nous dédions une part significative de notre travail à la comparaison entre les approches de synthèse et d'analyse. Nous défendons l'idée qu'en dépit de leur équivalence formelle, leurs propriétés computationnelles sont très différentes. En effet, en raison de la parcimonie héritée par la version discrétisée de l'EDP (incarnée par l'opérateur d'analyse), l'approche coparcimonieuse passe bien plus favorablement à l'échelle que le problème équivalent régularisé par parcimonie à la synthèse. Nos constatations sont illustrées dans le cadre de deux applications : la localisation de sources acoustiques, et la localisation de sources de crises épileptiques à partir de signaux électro-encéphalographiques. Dans les deux cas, nous vérifions que l'approche coparcimonieuse démontre de meilleures capacités de passage à l'échelle, au point qu'elle permet même une interpolation complète du champ de pression dans le temps et en trois dimensions. De plus, dans le cas des sources acoustiques, l'optimisation fondée sur le modèle d'analyse \emph{bénéficie} d'une augmentation du nombre de données observées, ce qui débouche sur une accélération du temps de traitement, plus rapide que l'approche de synthèse dans des proportions de plusieurs ordres de grandeur. Nos simulations numériques montrent que les méthodes développées pour les deux applications sont compétitives face à des algorithmes de localisation constituant l'état de l'art. Pour finir, nous présentons deux méthodes fondées sur la parcimonie à l'analyse pour l'estimation aveugle de la célérité du son et de l'impédance acoustique, simultanément à l'interpolation du champ sonore. Ceci constitue une étape importante en direction de la mise en œuvre de nos méthodes en en situation réelle<br>Inverse problems related to physical processes are of great importance in practically every field related to signal processing, such as tomography, acoustics, wireless communications, medical and radar imaging, to name only a few. At the same time, many of these problems are quite challenging due to their ill-posed nature. On the other hand, signals originating from physical phenomena are often governed by laws expressible through linear Partial Differential Equations (PDE), or equivalently, integral equations and the associated Green’s functions. In addition, these phenomena are usually induced by sparse singularities, appearing as sources or sinks of a vector field. In this thesis we primarily investigate the coupling of such physical laws with a prior assumption on the sparse origin of a physical process. This gives rise to a “dual” regularization concept, formulated either as sparse analysis (cosparse), yielded by a PDE representation, or equivalent sparse synthesis regularization, if the Green’s functions are used instead. We devote a significant part of the thesis to the comparison of these two approaches. We argue that, despite nominal equivalence, their computational properties are very different. Indeed, due to the inherited sparsity of the discretized PDE (embodied in the analysis operator), the analysis approach scales much more favorably than the equivalent problem regularized by the synthesis approach. Our findings are demonstrated on two applications: acoustic source localization and epileptic source localization in electroencephalography. In both cases, we verify that cosparse approach exhibits superior scalability, even allowing for full (time domain) wavefield interpolation in three spatial dimensions. Moreover, in the acoustic setting, the analysis-based optimization benefits from the increased amount of observation data, resulting in a speedup in processing time that is orders of magnitude faster than the synthesis approach. Numerical simulations show that the developed methods in both applications are competitive to state-of-the-art localization algorithms in their corresponding areas. Finally, we present two sparse analysis methods for blind estimation of the speed of sound and acoustic impedance, simultaneously with wavefield interpolation. This is an important step toward practical implementation, where most physical parameters are unknown beforehand. The versatility of the approach is demonstrated on the “hearing behind walls” scenario, in which the traditional localization methods necessarily fail. Additionally, by means of a novel algorithmic framework, we challenge the audio declipping problemregularized by sparsity or cosparsity. Our method is highly competitive against stateof-the-art, and, in the cosparse setting, allows for an efficient (even real-time) implementation
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Baysal, Arzu. "Inverse Problems For Parabolic Equations." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605623/index.pdf.

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In this thesis, we study inverse problems of restoration of the unknown function in a boundary condition, where on the boundary of the domain there is a convective heat exchange with the environment. Besides the temperature of the domain, we seek either the temperature of the environment in Problem I and II, or the coefficient of external boundary heat emission in Problem III and IV. An additional information is given, which is the overdetermination condition, either on the boundary of the domain (in Problem III and IV) or on a time interval (in Problem I and II). If solution of inverse problem exists, then the temperature can be defined everywhere on the domain at all instants. The thesis consists of six chapters. In the first chapter, there is the introduction where the definition and applications of inverse problems are given and definition of the four inverse problems, that we will analyze in this thesis, are stated. In the second chapter, some definitions and theorems which we will use to obtain some conclusions about the corresponding direct problem of our four inverse problems are stated, and the conclusions about direct problem are obtained. In the third, fourth, fifth and sixth chapters we have the analysis of inverse problems I, II, III and IV, respectively.
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Connolly, T. John. "Nonlinear methods for inverse problems." Thesis, University of Canterbury. Mathematics, 1989. http://hdl.handle.net/10092/8563.

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The general inverse problem is formulated as a nonlinear operator equation. The solution of this via the Newton-Kantorovich method is outlined. Fréchet differentiability of the operator is given by the implicit function theorem. We also consider questions such as uniqueness, stability and regularization of the inverse problem. This general theory is then applied to a number of different inverse problems. The Newton-Kantorovich method is derived for each example and Fréchet differentiability examined. In some cases numerical results are provided, for others our work provides a theoretical basis for results obtained by different authors. The problems considered include an interior measurement inverse problem from steady-state diffusion, and a boundary measurement problem for electrical conductivity imaging. We also examine the determination of refractive indices and scattering boundaries for the Helmholtz equation from measurements of the farfield. In addition an inverse problem from geometric optics is investigated.
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Stewart, K. A. "Inverse problems in signal processing." Thesis, University of Strathclyde, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382448.

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Aljohani, Hassan Musallam S. "Wavelet methods and inverse problems." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/18830/.

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Archaeological investigations are designed to acquire information without damaging the archaeological site. Magnetometry is one of the important techniques for producing a surface grid of readings, which can be used to infer underground features. The inversion of this data, to give a fitted model, is an inverse problem. This type of problem can be ill-posed or ill-conditioned, making the estimation of model parameters less stable or even impossible. More precisely, the relationship between archaeological data and parameters is expressed by a likelihood. It is not possible to use the standard regression estimate obtained through the likelihood, which means that no maximum likelihood estimate exists. Instead, various constraints can be added through a prior distribution with an estimate produced using the posterior distribution. Current approaches incorporate prior information describing smoothness, which is not always appropriate. The biggest challenge is that the reconstruction of an archaeological site as a single layer requires various physical features such as depth and extent to be assumed. By applying a smoothing prior in the analysis of stratigraphy data, however, these features are not easily estimated. Wavelet analysis has proved to be highly efficient at eliciting information from noisy data. Additionally, complicated signals can be explained by interpreting only a small number of wavelet coefficients. It is possible that a modelling approach, which attempts to describe an underlying function in terms of a multi-level wavelet representation will be an improvement on standard techniques. Further, a new method proposed uses an elastic-net based distribution as the prior. Two methods are used to solve the problem, one is based on one-stage estimation and the other is based on two stages. The one-stage considers two approaches a single prior for all wavelet resolution levels and a level-dependent prior, with separate priors at each resolution level. In a simulation study and a real data analysis, all these techniques are compared to several existing methods. It is shown that the methodology using a single prior provides good reconstruction, comparable even to several established wavelet methods that use mixture priors.
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Marroquin, J. L. (Jose Luis). "Probabilistic solution of inverse problems." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/15286.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1985.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.<br>Bibliography: p. 195-200.<br>by Jose Luis Marroquin.<br>Ph.D.
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Agapiou, Sergios. "Aspects of Bayesian inverse problems." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/60138/.

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The goal of this thesis is to contribute to the formulation and understanding of the Bayesian approach to inverse problems in function space. To this end we examine two important aspects of this approach: the frequentist asymptotic properties of the posterior, and the extraction of information from the posterior via sampling. We work in a separable Hilbert space setting and consider Gaussian priors on the unknown in conjugate Gaussian models. In the first part of this work we consider linear inverse problems with Gaussian additive noise and study the contraction in the small noise limit of the Gaussian posterior distribution to a Dirac measure centered on the true parameter underlying the data. In a wide range of situations, which include both mildly and severely ill-posed problems, we show how carefully calibrating the scaling of the prior as a function of the size of the noise, based on a priori known information on the regularity of the truth, yields optimal rates of contraction. In the second part we study the implementation in RN of hierarchical Bayesian linear inverse problems with Gaussian noise and priors, and with hyper-parameters introduced through the scalings of the prior and noise covariance operators. We use function space intuition to understand the large N behaviour of algorithms designed to sample the posterior and show that the two scaling hyper-parameters evolve under these algorithms in contrasting ways: as N grows the prior scaling slows down while the noise scaling speeds up. We propose a reparametrization of the prior scaling which is robust with respect to the increase in dimension. Our theory on the slowing down of the evolution of the prior scaling extends to hierarchical approaches in more general conjugate Gaussian settings, while our intuition covers other parameters of the prior covariance operator as well. Throughout the thesis we use a blend of results from measure theory and probability theory with tools from the theory of linear partial differential equations and numerical analysis.
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Books on the topic "Inverse problems"

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Talenti, Giorgio, ed. Inverse Problems. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/bfb0072658.

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Richter, Mathias. Inverse Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9.

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Richter, Mathias. Inverse Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9.

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Cannon, John Rozier, and Ulrich Hornung, eds. Inverse Problems. Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6.

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Kubo, Shiro, and Mini-Symposium on Inverse Problems (1992 : Hong Kong), eds. Inverse problems. Atlanta Technology Publications, 1992.

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Ramm, A. G. Inverse problems. Springer, 2005.

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Institute of Physics (Great Britain). Inverse problems. Institute of Physics, 1985.

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Chiachío-Ruano, Juan, Manuel Chiachío-Ruano, and Shankar Sankararaman. Bayesian Inverse Problems. CRC Press, 2021. http://dx.doi.org/10.1201/b22018.

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Gol’dman, N. L. Inverse Stefan Problems. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5488-8.

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Beilina, Larisa, ed. Applied Inverse Problems. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7816-4.

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Book chapters on the topic "Inverse problems"

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Richter, Mathias. "Characterization of Inverse Problems." In Inverse Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_1.

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Richter, Mathias. "Discretization of Inverse Problems." In Inverse Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_2.

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Richter, Mathias. "Regularization of Linear Inverse Problems." In Inverse Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_3.

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Richter, Mathias. "Regularization of Nonlinear Inverse Problems." In Inverse Problems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_4.

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Richter, Mathias. "Characterization of Inverse Problems." In Inverse Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_1.

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Richter, Mathias. "Discretization of Inverse Problems." In Inverse Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_2.

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Richter, Mathias. "Regularization of Linear Inverse Problems." In Inverse Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_3.

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Richter, Mathias. "Regularization of Nonlinear Inverse Problems." In Inverse Problems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_4.

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Anderssen, R. S. "The Linear Functional Strategy for Improperly Posed Problems." In Inverse Problems. Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6_1.

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Cannon, John R., and Salvador Pérez Esteva. "A Note on an Inverse Problem Related to the 3-D Heat Equation." In Inverse Problems. Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6_10.

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Conference papers on the topic "Inverse problems"

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Zhdanov, Michael. "Electromagnetic Inverse Problems." In 5th International Congress of the Brazilian Geophysical Society. European Association of Geoscientists & Engineers, 1997. http://dx.doi.org/10.3997/2214-4609-pdb.299.202.

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Baltes, H. P. "Inverse grating problems." In OSA Annual Meeting. Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.thd2.

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This review of current achievements in inverse scattering problems is focused on two exemplary problems: (1) from electromagnetic diffraction and (2) from statistical optics. (1) The question of uniqueness is illustrated in terms of the electromagnetic grating profile construction starting from prescribed diffraction efficiencies. The algorithm of Huiser and Baltes is revisited with respect to uniqueness, the incorporation of prior knowledge, and the transition from electromagnetic to Fourier optics. (2) Theoretical and experimental results are reviewed on the detection of diffractors such as phase gratings hidden behind a diffuser by means of optical correlation techniques. Experiments by Newman and Dainty verify the coherence effect predicted by Baltes et al., namely, the existence of a diffuser correlation length range where the diffraction orders of the phase grating disappear completely in a single broad intensity lobe but manifest themselves in the side peaks of the far-zone degree of coherence.
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Snieder, Roel. "Inverse Problems in Geophysics." In Signal Recovery and Synthesis. OSA, 2001. http://dx.doi.org/10.1364/srs.2001.sma2.

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"Inverse Problems and Synthesis." In 2018 XXIIIrd International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED). IEEE, 2018. http://dx.doi.org/10.1109/diped.2018.8543271.

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Jaeaeskelaeinen, Timo, and Markku Kuittinen. "Inverse grating diffraction problems." In Szklarska - DL tentative, edited by Jerzy Nowak and Marek Zajac. SPIE, 1991. http://dx.doi.org/10.1117/12.50118.

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"Inverse and Optimization Problems." In 10th International Conference on Mathematical Methods in Electromagnetic Theory, 2004. IEEE, 2004. http://dx.doi.org/10.1109/mmet.2004.1397075.

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"Inverse & nonlinear problems." In 2008 12th International Conference on Mathematical Methods in Electromagnetic Theory. IEEE, 2008. http://dx.doi.org/10.1109/mmet.2008.4580915.

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Tuncer, E. "Inverse problems in dielectrics." In 2011 IEEE 14th International Symposium on Electrets ISE 14. IEEE, 2011. http://dx.doi.org/10.1109/ise.2011.6084990.

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GOYAL, KAVITA, and MANI MEHRA. "WAVELETS AND INVERSE PROBLEMS." In Proceedings of the Satellite Conference of ICM 2010. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814338820_0015.

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Shinohara, Masaaki. "Inverse Problems in AHP." In International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 2014. http://dx.doi.org/10.13033/isahp.y2014.112.

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Reports on the topic "Inverse problems"

1

Santosa, Fadil. Inverse Problems in Nondestructive Evaluations. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada261370.

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Friedman, Avner. Inverse Problems in Wave Propagation. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada302229.

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Barhen, J., J. G. Berryman, L. Borcea, et al. Optimization and geophysical inverse problems. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/939130.

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Angell, T. S., and R. E. Kleinman. Inverse and Control Problems in Electromagnetics. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada292993.

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Gordon, Howard R. Inverse Problems in Hydrologic Radiative Transfer. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada629879.

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Colton, David, and Peter Monk. Inverse Scattering Problems for Electromagnetic Waves. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada337286.

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Michalski, Anatoli I. Inverse problems in demography and biodemography. Max Planck Institute for Demographic Research, 2006. http://dx.doi.org/10.4054/mpidr-wp-2006-041.

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Horowitz, Joel L. Ill-posed inverse problems in economics. Institute for Fiscal Studies, 2013. http://dx.doi.org/10.1920/wp.cem.2013.3713.

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Gordon, Howard R. Inverse Problems in Hydrologic Radiative Transfer. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada626577.

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Wolf, Emil. Direct and Inverse Problems in Statistical Wavefields. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/900275.

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