Дисертації з теми "Signal processing- models"
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Xu, Luzhou. "Growth curve models in signal processing applications." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0015020.
Повний текст джерелаLynch, Michael Richard. "Adaptive techniques in signal processing and connectionist models." Thesis, University of Cambridge, 1990. https://www.repository.cam.ac.uk/handle/1810/244884.
Повний текст джерелаRao, Tandhoni. "Noncausal methods and models for image." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/13344.
Повний текст джерелаBengtsson, Mats. "Antenna array signal processing for high rank data models." Doctoral thesis, KTH, Signaler, sensorer och system, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2903.
Повний текст джерелаNoland, Katy C. "Computational tonality estimation : signal processing and hidden Markov models." Thesis, Queen Mary, University of London, 2009. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8492.
Повний текст джерелаSaid, Maya Rida 1976. "Signal processing in biological cells : proteins, networks, and models." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/30165.
Повний текст джерелаIncludes bibliographical references (p. 202-210).
This thesis introduces systematic engineering principles to model, at different levels of abstraction the information processing in biological cells in order to understand the algorithms implemented by the signaling pathways that perform the processing. An example of how to emulate one of these algorithms in other signal processing contexts is also presented. At a high modeling level, the focus is on the network topology rather than the dynamical properties of the components of the signaling network. In this regime, we examine and analyze the distribution and properties of the network graph. Specifically, we present a global network investigation of the genotype/phenotype data-set recently developed for the yeast Saccharomyces cerevisiae from exposure to DNA damaging agents, enabling explicit study of how protein-protein interaction network characteristics may be associated with phenotypic functional effects. The properties of several functional yeast networks are also compared and a simple method to combine gene expression data with network information is proposed to better predict pathophysiological behavior. At a low level of modeling, the thesis introduces a new framework for modeling cellular signal processing based on interacting Markov chains. This framework provides a unified way to simultaneously capture the stochasticity of signaling networks in individual cells while computing a deterministic solution which provides average behavior. The use of this framework is demonstrated on two classical signaling networks: the mitogen activated protein kinase cascade and the bacterial chemotaxis pathway. The prospects of using cell biology as a metaphor for signal processing are also considered in a preliminary way by presenting a surface mapping algorithm based on bacterial chemotaxis.
by Maya Rida Said.
Sc.D.
Marmin, Arthur. "Rational models optimized exactly for solving signal processing problems." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG017.
Повний текст джерелаA wide class of nonconvex optimization problem is represented by rational optimization problems. The latter appear naturally in many areas such as signal processing or chemical engineering. However, finding the global optima of such problems is intricate. A recent approach called Lasserre's hierarchy provides a sequence of convex problems that has the theoretical guarantee to converge to the global optima. Nevertheless, this approach is computationally challenging due to the high dimensions of the convex relaxations. In this thesis, we tackle this challenge for various signal processing problems.First, we formulate the reconstruction of sparse signals as a rational optimization problem. We show that the latter has a structure that we wan exploit in order to reduce the complexity of the associated relaxations. We thus solve several practical problems such as the reconstruction of chromatography signals. We also extend our method to the reconstruction of various types of signal corrupted by different noise models.In a second part, we study the convex relaxations generated by our problems which take the form of high-dimensional semi-definite programming problems. We consider several algorithms mainly based on proximal operators to solve those high-dimensional problems efficiently.The last part of this thesis is dedicated to the link between polynomial optimization and symmetric tensor decomposition. Indeed, they both can be seen as an instance of the moment problem. We thereby propose a detection method as well as a decomposition algorithm for symmetric tensors based on the tools used in polynomial optimization. In parallel, we suggest a robust extraction method for polynomial optimization based on tensor decomposition algorithms. Those methods are illustrated on signal processing problems
Archer, Cynthia. "A framework for representing non-stationary data with mixtures of linear models /." Full text open access at:, 2002. http://content.ohsu.edu/u?/etd,585.
Повний текст джерелаLiu, Li. "Ground vehicle acoustic signal processing based on biological hearing models." College Park, Md. : University of Maryland, 1999. http://techreports.isr.umd.edu/reports/1999/MS%5F99-6.pdf.
Повний текст джерелаThesis research directed by Institute for Systems Research. "M.S. 99-6." Includes bibliographical references (leaves 75-78). Available also online as a PDF file via the World Wide Web.
Boman, Katarina. "Low-angle estimation : Models, methods and bounds." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-85998.
Повний текст джерелаMahata, Kaushik. "Identification of dynamic errors-in-variables models." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86301.
Повний текст джерелаWebb, M. R. "Millimetre wave quasi-optical signal processing systems." Thesis, University of St Andrews, 1993. http://hdl.handle.net/10023/2827.
Повний текст джерелаFabrizio, Giuseppe Aureliano. "Space-time characterisation and adaptive processing of ionospherically-propagated HF signals /." Title page, table of contents and abstract only, 2000. http://web4.library.adelaide.edu.au/theses/09PH/09phf129.pdf.
Повний текст джерелаGlenn, Dickins, and glenn dickins@dolby com. "Applications of Continuous Spatial Models in Multiple Antenna Signal Processing." The Australian National University. Research School of Information Sciences and Engineering, 2008. http://thesis.anu.edu.au./public/adt-ANU20080702.222814.
Повний текст джерелаMahata, Kaushik. "Estimation Using Low Rank Signal Models." Doctoral thesis, Uppsala University, Department of Information Technology, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3844.
Повний текст джерелаDesigning estimators based on low rank signal models is a common practice in signal processing. Some of these estimators are designed to use a single low rank snapshot vector, while others employ multiple snapshots. This dissertation deals with both these cases in different contexts.
Separable nonlinear least squares is a popular tool to extract parameter estimates from a single snapshot vector. Asymptotic statistical properties of the separable non-linear least squares estimates are explored in the first part of the thesis. The assumptions imposed on the noise process and the data model are general. Therefore, the results are useful in a wide range of applications. Sufficient conditions are established for consistency, asymptotic normality and statistical efficiency of the estimates. An expression for the asymptotic covariance matrix is derived and it is shown that the estimates are circular. The analysis is extended also to the constrained separable nonlinear least squares problems.
Nonparametric estimation of the material functions from wave propagation experiments is the topic of the second part. This is a typical application where a single snapshot vector is employed. Numerical and statistical properties of the least squares algorithm are explored in this context. Boundary conditions in the experiments are used to achieve superior estimation performance. Subsequently, a subspace based estimation algorithm is proposed. The subspace algorithm is not only computationally efficient, but is also equivalent to the least squares method in accuracy.
Estimation of the frequencies of multiple real valued sine waves is the topic in the third part, where multiple snapshots are employed. A new low rank signal model is introduced. Subsequently, an ESPRIT like method named R-Esprit and a weighted subspace fitting approach are developed based on the proposed model. When compared to ESPRIT, R-Esprit is not only computationally more economical but is also equivalent in performance. The weighted subspace fitting approach shows significant improvement in the resolution threshold. It is also robust to additive noise.
Cai, Qin. "Detecting Chaotic Signals with Nonlinear Models." PDXScholar, 1993. https://pdxscholar.library.pdx.edu/open_access_etds/4564.
Повний текст джерелаClark, Laurence. "A distributed information processing model of bacterial chemotaxis." Thesis, University of Liverpool, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367071.
Повний текст джерелаSun, David. "Optical signal processors: novel computer models and experiments." Thesis, Virginia Tech, 1994. http://hdl.handle.net/10919/42233.
Повний текст джерелаMaster of Science
Yu, Kai. "Multiple-Input Multiple-Output Radio Propagation Channels : Characteristics and Models." Doctoral thesis, Stockholm, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138.
Повний текст джерелаYang, Yang. "2D signal processing: efficient models for spectral compressive sensing & single image reflection suppression." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6667.
Повний текст джерелаMeyer, Georg. "Models of neurons in the ventral cochlear nucleus : signal processing and speech recognition." Thesis, Keele University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334715.
Повний текст джерелаZhang, Zhiguo, and 張治國. "On bandwidth and scale selection in processing of time-varying signalswith applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39707465.
Повний текст джерелаWang, Xiaofeng. "Simulation models for rolling bearing vibration generation and fault detection via neural networks." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362159.
Повний текст джерелаWong, Hau San. "Adaptive image processing using computational intelligence techniques." Thesis, The University of Sydney, 1998. https://hdl.handle.net/2123/27658.
Повний текст джерелаSelén, Yngve. "Model selection /." Uppsala : Univ. : Dept. of Information Technology, Univ, 2004. http://www.it.uu.se/research/reports/lic/2004-003/.
Повний текст джерелаPerry, Stuart William. "Adaptive image restoration perception based neural network models and algorithms /." Connect to full text, 1998. http://hdl.handle.net/2123/389.
Повний текст джерелаTitle from title screen (viewed Apr. 16, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Electrical and Information Engineering, Faculty of Engineering. Degree awarded 1999; thesis submitted 1998. Includes bibliography. Also available in print form.
Lannerhed, Petter. "Structural Diagnosis Implementation of Dymola Models using Matlab Fault Diagnosis Toolbox." Thesis, Linköpings universitet, Fordonssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138753.
Повний текст джерелаStoffell, Kevin M. "Implementation of a Quadrature Mirror Filter Bank on an SRC reconfigurable computer for real-time signal processing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FStoffell.pdf.
Повний текст джерелаThesis Advisor(s): Douglas J. Fouts. "September 2006." Includes bibliographical references (p. 111-112). Also available in print.
Hong, Jung. "Statistical Parametric Models and Inference for Biomedical Signal Processing: Applications in Speech and Magnetic Resonance Imaging." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10074.
Повний текст джерелаEngineering and Applied Sciences
Arnold, Dieter M. "Computing information rates of finite-state models with application to magnetic recording /." Konstanz : Hartung-Gorre, 2003. http://www.loc.gov/catdir/toc/fy0609/2005530413.html.
Повний текст джерелаHymel, Shawn. "Massively Parallel Hidden Markov Models for Wireless Applications." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/36017.
Повний текст джерелаMaster of Science
Jonsson, Patrik. "Surface Status Classification, Utilizing Image Sensor Technology and Computer Models." Doctoral thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-24828.
Повний текст джерелаWigren, Anna. "Exploiting conjugacy in state-space models with sequential Monte Carlo." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-429236.
Повний текст джерелаLi, Xiao, and 李驍. "Channel estimation and timing synchronization in cooperative communication systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42841835.
Повний текст джерелаSelli, Giuseppe. "BGA footprints modeling and physics based via models validation for power and signal integrity applications." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.umr.edu/thesis/pdf/Selli_09007dcc8040f1b6.pdf.
Повний текст джерелаVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 7, 2007). Includes bibliographical references.
Sayeed, Taufique. "Methods and models in signal processing for gait analysis using waist-worn accelerometer : a contribution to Parkinson’s disease." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/317390.
Повний текст джерелаLa enfermedad de Parkinson (EP) es una enfermedad neurodegenerativa que altera, de forma predominante, la capacidad motora de los pacientes y, además, afecta la velocidad, la automaticidad y la fluidez de los movimientos naturales. Tras varios años, los pacientes fluctúan entre unos periodos en los cuales pueden moverse de forma casi normal durante varias horas (periodos o estados ON) y periodos donde los desórdenes del movimiento aparecen (periodos o estados OFF). Entre otros síntomas, los pacientes con la EP sufren una reducción de la longitud del paso y una inhabilitación de la marcha. Monitorizar la longitud del paso contribuye a inferir el estado motor de los pacientes, a conocer las fluctuaciones durante su vida diaria y, en consecuencia, permitiría a los neurólogos realizar un seguimiento de la evolución de la enfermedad y mejorar la pauta terapéutica. En este sentido, los acelerómetros MEMS pueden ser usados para detectar pasos y estimar la longitud del paso más allá de las instalaciones de los laboratorios, es decir, en entornos no controlados. Esta tesis presenta las contribuciones originales del autor en el campo del análisis del movimiento humano basado en acelerómetros MEMS, específicamente en la detección de pasos y la estimación de la longitud del paso en pacientes con la EP. En esta tesis, se ha seleccionado una posición amigable en la cual localizar un acelerómetro MEMS triaxial. La posición, que consiste en el lateral de la cintura cerca de la cresta ilíaca, fue seleccionada para mejorar la comodidad y la aceptabilidad desde el punto de vista del paciente. Asumiendo esta posición, en primer lugar, se presenta un análisis de los distintos métodos existentes en la literatura para la detección de pasos y, además, se presenta una nueva técnica de detección. Los métodos se han testado en usuarios sanos y en pacientes con Parkinson, mostrando que el nuevo método obtiene un porcentaje de acierto en la detección más alto que el resto de métodos. En segundo lugar, se han seleccionado aquellos métodos de estimación de la longitud de paso que fueron desarrollados mediante un sensor situado en el centro de la espalda, cerca de las vértebras L4-L5. Estos métodos fueron modificados con el fin de ser adaptados a la nueva posición del sensor y validados en señales obtenidas de 25 pacientes con EP. Además, se propone un factor de corrección genérico, el cual se compara con el mejor de los métodos obtenidos, para ser usado en lugar de una calibración individual. A pesar de la variabilidad en la velocidad de la marcha debida a las fluctuaciones motoras, el nuevo método alcanza un 96,76% de precisión en la detección de pasos y, respecto la estimación de la longitud del paso, los métodos modificados obtienen mayor precisión que los originales. El mejor de los métodos obtenidos consiste en el uso de un factor de corrección multiplicador que considera los pasos de cada lado por separado, proporcionando un error medio de 0,03 m. Finalmente, se presenta un nuevo modelo de la marcha representada como un péndulo invertido modificado que se emplea para analizar las señales de acelerometría obtenidas desde el lateral izquierdo de la cintura. De forma más concreta, este modelo considera el desplazamiento vertical de la cadera como un péndulo invertido durante el paso derecho (lado contrario del sensor). Para el paso izquierdo, el desplazamiento durante la fase single support y double support se model iza como un péndulo invertido y un péndulo simple, respectivamente. Los resultados obtenidos en 25 pacientes con EP son presentados y discutidos. La validez y fiabilidad del nuevo modelo son comparados con tres modelos distintos. Los resultados experimentales obtenidos muestran que el nuevo modelo, llamado ICE-CETpD, estima la longitud del paso con una precisión mayor que el resto de métodos seleccionados de la literatura. El error promedio de este método durante el estado OFF y ON es de 0,021 m. y 0,029 m., respectivamente, con una correlación intraclase superior a 0.9 en ambos estados motores. La calibración de los parámetros del modelo en cada estado motor ha sido evaluada, concluyendo que una calibración en ON proporciona más precisión en los resultados. En consecuencia, la ventaja de la aproximación propuesta residiría en no requerir señales en OFF de los pacientes con EP, por lo cual no sería necesario que los pacientes prescindieran de tomas de medicación.
La malaltia de Parkinson (MP) és una malaltia neurodegenerativa que altera de forma predominant la capacitat motora dels pacients i, a més, afecta la velocitat, l’automatització i la fluïdesa dels moviments naturals. Després de diversos anys, els pacients fluctuen entre uns períodes en els quals poden moure’s de forma quasi normal i que duren vàries hores (períodes o estats ON) i períodes on els desordres del moviment apareixen (períodes o estats OFF). Entre altres símptomes, els pacients amb la MP sofreixen una reducció de la longitud del pas i una inhabilitació de la marxa. La monitorització de la longitud del pas contribueix a inferir l’estat motor del pacient i a conèixer les fluctuacions durant la seva vida diària permetent als neuròlegs, en conseqüència, realitzar un seguiment de l’evolució de la malaltia i millorar la pauta terapèutica. En aquest sentit, els acceleròmetres MEMS poden ser utilitzats per tal de detectar passes i estimar la longitud del pas fora de les instal·lacions dels laboratoris, és a dir, en entorns no controlats. Aquesta tesis presenta les contribucions originals de l’autor en el camp de l’anàlisi del moviment humà basat en acceleròmetres MEMS, específicament en la detecció de passes i l’estimació de la longitud del pas en pacients amb MP. En aquesta tesis, s’ha seleccionat una posició amigable en la qual localitzar un acceleròmetre MEMS triaxial. La posició, que consisteix en el lateral de la cintura prop de la cresta ilíaca, va ser seleccionada per maximitzar la comoditat i l’acceptabilitat des del punt de vista del pacient. Assumint aquesta posició, en primer lloc, es presenta un anàlisi dels diferents mètodes existents a la literatura en detecció de passes i, a més, es presenta una nova tècnica de detecció basada en acceleròmetres. Tots els mètodes han estat provats en usuaris sans i en pacients amb la MP; els resultats mostren que el nou mètode obté un percentatge d’encert en la detecció de passes més alt que la resta de mètodes. En segon lloc, s’han seleccionat aquells mètodes d’estimació de la longitud de pas que van ser desenvolupats per a tractar les senyals d’un sensor situat prop de les vèrtebres L4-L5. Aquests mètodes van ser modificats amb la fi de ser adaptats a la nova posició del sensor. Tots ells van ser validats en senyals obtingudes de 25 pacients amb la MP. A més, es proposa un factor de correcció genèric, el qual es compara amb el millor dels mètodes obtinguts per tal de ser usat en lloc d’una calibració individual. A pesar de la variabilitat en la velocitat de la marxa deguda a les fluctuacions motores, el nou mètode assoleix un 96,76% de precisió en la detecció de passes i, respecte l’estimació de la longitud de pas, els mètodes modificats obtenen una major precisió que els originals. El millor d’ells consisteix en un factor de correcció multiplicador que considera les passes de cada costat per separat, proporcionant un error mig de 0,033 m. Finalment, es presenta un nou model de la marxa representada com un pèndul invertit modificat que és utilitzat per analitzar les senyals d’accelerometria obtingudes des del lateral esquerra de la cintura. De forma més concreta, aquest model considera el desplaçament vertical del maluc com un pèndul invertit durant la passa dreta (costat contrari al del sensor). Durant la passa esquerra, el desplaçament durant la fase single suport i double suport es modelitza com un pèndul invertit i un pèndul simple, respectivament. Els resultats obtinguts en 25 pacients amb MP són presentats i discutits. La validesa i fiabilitat del nou model són comparats amb els de tres models diferents. Els resultats experimentals obtinguts mostren que el nou model, anomenat ICE—CETpD, estima la longitud de la passa amb una major precisió que la resta de mètodes seleccionats de la literatura. L’error mitjà d’aquest mètode durant l’estat OFF i ON és de 0, 021 i 0,029 m., respectivament, amb una correlació intraclasse superior a 0,9 en ambdós estats motors. La calibració dels paràmetres del model en cada estat motor ha estat avaluada, obtenint que una calibració en ON proporciona més precisió en els resultats. D’aquesta manera, l’avantatge de l’aproximació proposada residiria en no requerir de senyals en OFF dels pacients amb MP, per la qual cosa no seria necessari que els pacients prescindissin de preses de medicació.
Lockowandt, Karin. "Parsing and Validation of Modelica Models Utilising Fault Diagnosis." Thesis, Linköpings universitet, Fordonssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-137542.
Повний текст джерелаChen, Xin. "Ensemble methods in large vocabulary continuous speech recognition." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/5797.
Повний текст джерелаThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 28, 2008) Vita. Includes bibliographical references.
Santos, Diliana Maria Barradas Rebelo dos. "Human activity recognition for an intelligent knee orthosis." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8493.
Повний текст джерелаActivity recognition with body-worn sensors is a large and growing field of research. In this thesis we evaluate the possibility to recognize human activities based on data from biosignal sensors solely placed on or under an existing passive knee orthosis, which will produce the needed information to integrate sensors into the orthosis in the future. The development of active orthotic knee devices will allow population to ambulate in a more natural, efficient and less painful manner than they might with a traditional orthosis. Thus, the term ’active orthosis’ refers to a device intended to increase the ambulatory ability of a person suffering from a knee pathology by applying forces to correct the position only when necessary and thereby make usable over longer periods of time. The contribution of this work is the evaluation of the ability to recognize activities with these restrictions on sensor placement as well as providing a proof-of-concept for the development of an activity recognition system for an intelligent orthosis. We use accelerometers and a goniometer placed on the orthosis and Electromyography (EMG) sensors placed on the skin under the orthosis to measure motion and muscle activity respectively. We segment signals in motion primitives semi-automatically and apply Hidden-Markov-Models (HMM) to classify the isolated motion primitives. We discriminate between seven activities like for example walking stairs up and ascend a hill. In a user study with six participants, we evaluate the systems performance for each of the different biosignal modalities alone as well as the combinations of them. For the best performing combination, we reach an average person-dependent accuracy of 98% and a person-independent accuracy of 79%.
Ablin, Pierre. "Exploration of multivariate EEG /MEG signals using non-stationary models." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT051.
Повний текст джерелаIndependent Component Analysis (ICA) models a set of signals as linear combinations of independent sources. This analysis method plays a key role in electroencephalography (EEG) and magnetoencephalography (MEG) signal processing. Applied on such signals, it allows to isolate interesting brain sources, locate them, and separate them from artifacts. ICA belongs to the toolbox of many neuroscientists, and is a part of the processing pipeline of many research articles. Yet, the most widely used algorithms date back to the 90's. They are often quite slow, and stick to the standard ICA model, without more advanced features.The goal of this thesis is to develop practical ICA algorithms to help neuroscientists. We follow two axes. The first one is that of speed. We consider the optimization problems solved by two of the most widely used ICA algorithms by practitioners: Infomax and FastICA. We develop a novel technique based on preconditioning the L-BFGS algorithm with Hessian approximation. The resulting algorithm, Picard, is tailored for real data applications, where the independence assumption is never entirely true. On M/EEG data, it converges faster than the `historical' implementations.Another possibility to accelerate ICA is to use incremental methods, which process a few samples at a time instead of the whole dataset. Such methods have gained huge interest in the last years due to their ability to scale well to very large datasets. We propose an incremental algorithm for ICA, with important descent guarantees. As a consequence, the proposed algorithm is simple to use and does not have a critical and hard to tune parameter like a learning rate.In a second axis, we propose to incorporate noise in the ICA model. Such a model is notoriously hard to fit under the standard non-Gaussian hypothesis of ICA, and would render estimation extremely long. Instead, we rely on a spectral diversity assumption, which leads to a practical algorithm, SMICA. The noise model opens the door to new possibilities, like finer estimation of the sources, and use of ICA as a statistically sound dimension reduction technique. Thorough experiments on M/EEG datasets demonstrate the usefulness of this approach.All algorithms developed in this thesis are open-sourced and available online. The Picard algorithm is included in the largest M/EEG processing Python library, MNE and Matlab library, EEGlab
Nilsson, Mats. "Building Reconstruction of Digital Height Models with the Markov Chain Monte Carlo Method." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148886.
Повний текст джерела洪觀宇 and Roy Hung. "Time domain analysis and synthesis of cello tones based on perceptual quality and playing gestures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215348.
Повний текст джерелаDi, Mauro Mario. "Statistical models for the characterization, identification and mitigation of distributed attacks in data networks." Doctoral thesis, Universita degli studi di Salerno, 2018. http://hdl.handle.net/10556/3088.
Повний текст джерелаThe thesis focuses on statistical approaches to model, mitigate, and prevent distributed network attacks. When dealing with distributed network attacks (and, more in general, with cyber-security problems), three fundamental phases/issues emerge distinctly. The first issue concerns the threat propagation across the network, which entails an "avalanche" effect, with the number of infected nodes increasing exponentially as time elapses. The second issue regards the design of proper mitigation strategies (e.g., threat detection, attacker's identification) aimed at containing the propagation phenomenon. Finally (and this is the third issue), it is also desirable to act on the system infrastructure to grant a conservative design by adding some controlled degree of redundancy, in order to face those cases where the attacker has not been yet defeated. The contributions of the present thesis address the aforementioned relevant issues, namely, propagation, mitigation and prevention of distributed network attacks. A brief summary of the main contributions is reported below. The first contribution concerns the adoption of Kendall’s birth-and-death process as an analytical model for threat propagation. Such a model exhibits two main properties: i) it is a stochastic model (a desirable requirement to embody the complexity of real-world networks) whereas many models are purely deterministic; ii) it is able to capture the essential features of threat propagation through a few parameters with a clear physical meaning. By exploiting the remarkable properties of Kendall’s model, the exact solution for the optimal resource allocation problem (namely, the optimal mitigation policy) has been provided for both conditions of perfectly known parameters, and unknown parameters (with the latter case being solved through a Maximum-Likelihood estimator). The second contribution pertains to the formalization of a novel kind of randomized Distributed Denial of Service (DDoS) attack. In particular, a botnet (a network of malicious entities) is able to emulate some normal traffic, by picking messages from a dictionary of admissible requests. Such a model allows to quantify the botnet “learning ability”, and to ascertain the real nature of users (normal or bot) via an indicator referred to as MIR (Message Innovation Rate). Exploiting the considered model, an algorithm that allows to identify a botnet (possibly) hidden in the network has been devised. The results are then extended to the case of a multi-cluster environment, where different botnets are concurrently present in the network, and an algorithm to identify the different clusters is conceived. The third contribution concerns the formalization of the network resilience problem and the consequent design of a prevention strategy. Two statistical frameworks are proposed to model the high availability requirements of network infrastructures, namely, the Stochastic Reward Network (SRN), and the Universal Generating Function (UGF) frameworks. In particular, since in the network environment dealing with multidimensional quantities is crucial, an extension of the classic UGF framework, called Multi-dimensional UGF (MUGF), is devised. [edited by author]
XVI n.s.
Al-Muhtaseb, Husni A., Sabri A. Mahmoud, and Rami S. R. Qahwaji. "Recognition of off-line printed Arabic text using Hidden Markov Models." Elsevier, 2008. http://hdl.handle.net/10454/4105.
Повний текст джерелаThis paper describes a technique for automatic recognition of off-line printed Arabic text using Hidden Markov Models. In this work different sizes of overlapping and non-overlapping hierarchical windows are used to generate 16 features from each vertical sliding strip. Eight different Arabic fonts were used for testing (viz. Arial, Tahoma, Akhbar, Thuluth, Naskh, Simplified Arabic, Andalus, and Traditional Arabic). It was experimentally proven that different fonts have their highest recognition rates at different numbers of states (5 or 7) and codebook sizes (128 or 256). Arabic text is cursive, and each character may have up to four different shapes based on its location in a word. This research work considered each shape as a different class, resulting in a total of 126 classes (compared to 28 Arabic letters). The achieved average recognition rates were between 98.08% and 99.89% for the eight experimental fonts. The main contributions of this work are the novel hierarchical sliding window technique using only 16 features for each sliding window, considering each shape of Arabic characters as a separate class, bypassing the need for segmenting Arabic text, and its applicability to other languages.
Rastgoufard, Rastin. "The Interacting Multiple Models Algorithm with State-Dependent Value Assignment." ScholarWorks@UNO, 2012. http://scholarworks.uno.edu/td/1477.
Повний текст джерелаKelsall, A. "Flexible Shape Models for Marine Animal Detection in Underwater Images." Thesis, Honours thesis, University of Tasmania, 2005. https://eprints.utas.edu.au/248/1/afkThesis_FINAL.pdf.
Повний текст джерелаVono, Maxime. "Asymptotically exact data augmentation : models and Monte Carlo sampling with applications to Bayesian inference." Thesis, Toulouse, INPT, 2020. http://www.theses.fr/2020INPT0098.
Повний текст джерелаNumerous machine learning and signal/image processing tasks can be formulated as statistical inference problems. As an archetypal example, recommendation systems rely on the completion of partially observed user/item matrix, which can be conducted via the joint estimation of latent factors and activation coefficients. More formally, the object to be inferred is usually defined as the solution of a variational or stochastic optimization problem. In particular, within a Bayesian framework, this solution is defined as the minimizer of a cost function, referred to as the posterior loss. In the simple case when this function is chosen as quadratic, the Bayesian estimator is known to be the posterior mean which minimizes the mean square error and defined as an integral according to the posterior distribution. In most real-world applicative contexts, computing such integrals is not straightforward. One alternative lies in making use of Monte Carlo integration, which consists in approximating any expectation according to the posterior distribution by an empirical average involving samples from the posterior. This so-called Monte Carlo integration requires the availability of efficient algorithmic schemes able to generate samples from a desired posterior distribution. A huge literature dedicated to random variable generation has proposed various Monte Carlo algorithms. For instance, Markov chain Monte Carlo (MCMC) methods, whose particular instances are the famous Gibbs sampler and Metropolis-Hastings algorithm, define a wide class of algorithms which allow a Markov chain to be generated with the desired stationary distribution. Despite their seemingly simplicity and genericity, conventional MCMC algorithms may be computationally inefficient for large-scale, distributed and/or highly structured problems. The main objective of this thesis consists in introducing new models and related MCMC approaches to alleviate these issues. The intractability of the posterior distribution is tackled by proposing a class of approximate but asymptotically exact augmented (AXDA) models. Then, two Gibbs samplers targetting approximate posterior distributions based on the AXDA framework, are proposed and their benefits are illustrated on challenging signal processing, image processing and machine learning problems. A detailed theoretical study of the convergence rates associated to one of these two Gibbs samplers is also conducted and reveals explicit dependences with respect to the dimension, condition number of the negative log-posterior and prescribed precision. In this work, we also pay attention to the feasibility of the sampling steps involved in the proposed Gibbs samplers. Since one of this step requires to sample from a possibly high-dimensional Gaussian distribution, we review and unify existing approaches by introducing a framework which stands for the stochastic counterpart of the celebrated proximal point algorithm. This strong connection between simulation and optimization is not isolated in this thesis. Indeed, we also show that the derived Gibbs samplers share tight links with quadratic penalty methods and that the AXDA framework yields a class of envelope functions related to the Moreau one
Barry, Brendan(Brendan Cael). "Distributional models of ocean carbon export." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122321.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 137-153).
Each year, surface ocean ecosystems export sinking particles containing gigatons of carbon into the ocean's interior. This particle flux connects the entire ocean microbiome and constitutes a fundamental aspect of marine microbial ecology and biogeochemical cycles. Particle flux is also variable and intricately complex, impeding its mechanistic or quantitative description. In this thesis we pair compilations of available data with novel mathematical models to explore the relationships between particle flux and other key variables - temperature, net primary production, and depth. Particular use is made of (probability) distributional descriptions of quantities that are known to vary appreciably. First, using established thermodynamic dependencies for primary production and respiration, a simple mechanistic model is developed relating export efficiency (i.e. the fraction of primary production that is exported out of the surface ocean via particle flux) to temperature.
The model accounts for the observed variability in export efficiency due to temperature without idealizing out the remaining variability that evinces particle flux's complexity. This model is then used to estimate the metabolically-driven change in average export efficiency over the era of long-term global sea surface temperature records, and it is shown that the underlying mechanism may help explain glacial-interglacial atmospheric carbon dioxide drawdown. The relationship between particle flux and net primary production is then explored. Given that these are inextricable but highly variable and measured on different effective scales, it is hypothesized that a quantitative relationship emerges between collections of the two measurements - i.e. that they can be related not measurement-by-measurement but rather via their probability distributions.
It is shown that on large spatial or temporal scales both are consistent with lognormal distributions, as expected if each is considered as the collective result of many subprocesses. A relationship is then derived between the log-moments of their distributions and agreement is found between independent estimates of this relationship, suggesting that upper ocean particle flux is predictable from net primary production on large spatiotemporal scales. Finally, the attenuation of particle flux with depth is explored. It is shown that while several particle flux-versus-depth models capture observations equivalently, these carry very different implications mechanistically and for magnitudes of export out of the surface ocean. A model is then proposed for this relationship that accounts for measurements of both the flux profile and of the settling velocity distribution of particulate matter, and is thus more consistent with and constrained by empirical knowledge.
Possible future applications of these models are discussed, as well as how they could be tested and/or constrained observationally.
by Brendan Barry.
Ph. D.
Ph.D. Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution)
Bengtsson, Jerker. "Models and Methods for Development of DSP Applications on Manycore Processors." Doctoral thesis, Högskolan i Halmstad, Centrum för forskning om inbyggda system (CERES), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-14706.
Повний текст джерелаLoscos, Àlex. "Spectral processing of the singing voice." Doctoral thesis, Universitat Pompeu Fabra, 2007. http://hdl.handle.net/10803/7542.
Повний текст джерелаLa tesi presenta nous procediments i formulacions per a la descripció i transformació d'aquells atributs específicament vocals de la veu cantada. La tesis inclou, entre d'altres, algorismes per l'anàlisi i la generació de desordres vocals como ara rugositat, ronquera, o veu aspirada, detecció i modificació de la freqüència fonamental de la veu, detecció de nasalitat, conversió de veu cantada a melodia, detecció de cops de veu, mutació de veu cantada, i transformació de veu a instrument; exemplificant alguns d'aquests algorismes en aplicacions concretes.
Esta tesis doctoral versa sobre el procesado digital de la voz cantada, más concretamente, sobre el análisis, transformación y síntesis de este tipo de voz basándose e dominio espectral, con especial énfasis en aquellas técnicas relevantes para el desarrollo de aplicaciones musicales.
La tesis presenta nuevos procedimientos y formulaciones para la descripción y transformación de aquellos atributos específicamente vocales de la voz cantada. La tesis incluye, entre otros, algoritmos para el análisis y la generación de desórdenes vocales como rugosidad, ronquera, o voz aspirada, detección y modificación de la frecuencia fundamental de la voz, detección de nasalidad, conversión de voz cantada a melodía, detección de los golpes de voz, mutación de voz cantada, y transformación de voz a instrumento; ejemplificando algunos de éstos en aplicaciones concretas.
This dissertation is centered on the digital processing of the singing voice, more concretely on the analysis, transformation and synthesis of this type of voice in the spectral domain, with special emphasis on those techniques relevant for music applications.
The thesis presents new formulations and procedures for both describing and transforming those attributes of the singing voice that can be regarded as voice specific. The thesis includes, among others, algorithms for rough and growl analysis and transformation, breathiness estimation and emulation, pitch detection and modification, nasality identification, voice to melody conversion, voice beat onset detection, singing voice morphing, and voice to instrument transformation; being some of them exemplified with concrete applications.