Download or read book SEGMENTATION NON SUPERVISEE D IMAGES MULTI SPECTRALES PAR CHAINES DE MARKOV CACHEES written by Nathalie Giordana and published by . This book was released on 1996 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: CETTE THESE EST CONSACREE A LA SEGMENTATION NON SUPERVISEE D'IMAGES MULTI-SPECTRALES PAR CHAINES DE MARKOV CACHEES ET PLUS PARTICULIEREMENT A L'ETUDE DE L'ETAPE D'ESTIMATION. L'OBJET DE CE TRAVAIL EST DE CONCEVOIR DES METHODES PERMETTANT D'ESTIMER DES MELANGES DE LOIS GENERALISES. CES METHODES D'ESTIMATION FONDEES SUR L'ALGORITHME ICE PERMETTENT DE DETECTER PARMI UN ENSEMBLE DE LOIS, CELLES QUI SONT LE PLUS FIDELES A LA REALITE ET D'ESTIMER LES PARAMETRES CORRESPONDANT A CHACUNE DES LOIS DETECTEES. LES ETUDES COMPARATIVES DES DIFFERENTES METHODES MISES AU POINT AVEC LES METHODES CLASSIQUES EM ET ICE, SUR DES CHAINES SIMULEES PUIS SUR DES IMAGES, MONTRENT L'EFFICACITE DES ALGORITHMES GENERALISES. NOUS ETUDIONS EGALEMENT LA SEGMENTATION MULTI-SPECTRALE EN CONSIDERANT DES CANAUX INDEPENDANTS POUR TRAITER LES MELANGES GENERALISES ET DES CANAUX CORRELES DANS LE CAS DE MELANGES GAUSSIENS. NOUS METTONS AINSI EN EVIDENCE L'INTERET OU NON DE L'AJOUT DE CANAUX D'OBSERVATIONS. DANS CE CADRE DE LA FUSION DE DONNEES, NOUS NOUS INTERESSONS A LA THEORIE DE L'EVIDENCE. NOUS INTRODUISONS ALORS LA NOTION DE CHAINE DE MARKOV CACHEE EVIDENTIELLE ET NOUS DEVELOPPONS LES METHODES DE SEGMENTATION QUI LUI SONT ASSOCIEE. LES ETUDES EFFECTUEES SUR DES CHAINES MONTRENT L'INTERET DE CETTE MODELISATION MAIS EGALEMENT SES DIFFICULTES DE MISE EN UVRE DANS UN CADRE NON SUPERVISEE

Download or read book CHAINES DE MARKOV CACHEES ET SEGMENTATION NON SUPERVISEE DE SEQUENCES D IMAGES written by BTISSAM.. BENMILOUD and published by . This book was released on 1994 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: CETTE THESE EST CONSACREE A LA SEGMENTATION NON SUPERVISEE DES SEQUENCES D'IMAGES DANS LE CADRE DES MODELISATIONS PAR CHAINES DE MARKOV CACHEES. NOUS METTONS L'ACCENT SUR LA PHASE D'ESTIMATION DES PARAMETRES, PREALABLE A LA PHASE DE SEGMENTATION. NOUS PROPOSONS PLUSIEURS ALGORITHMES ORIGINAUX D'ESTIMATION DES PARAMETRES OBTENUS A PARTIR DES METHODES ITERATIVE CONDITIONAL ESTIMATION ET STOCHASTIC ESTIMATION MAXIMISATION. NOUS MONTRONS LEUR COMPETITIVITE VIS A VIS DE L'ALGORITHME ESTIMATION MAXIMISATION, LE PLUS FREQUEMMENT UTILISE POUR L'IDENTIFICATION DES CHAINES DE MARKOV CACHEES DANS DIFFERENTS CAS D'HOMOGENEITE ET DE BRUITAGE DES CHAINES. UNE ETUDE DU COMPORTEMENT DE CES DIFFERENTS ESTIMATEURS COMBINES AVEC LA METHODE MAXIMUM POSTERIOR MODE EST EGALEMENT EFFECTUEE SUR PLUSIEURS CHAINES SIMULEES. NOUS APPLIQUONS ENSUITE LES MEMES ALGORITHMES SUR DES IMAGES SIMULEES OU REELLES. NOUS TRANSFORMONS L'IMAGE EN PROCESSUS MONO DIMENSIONNEL GRACE AU PARCOURS DE PEANO. NOUS BENEFICIONS AINSI DE METHODES SOUPLES ET RAPIDES POUR LA SEGMENTATION NON SUPERVISEE DES IMAGES. NOUS ETUDIONS EGALEMENT LA SEGMENTATION LOCALE DANS LE CAS DES CHAINES DE MARKOV CACHEES, EN TENANT COMPTE D'UN CERTAIN NOMBRE DE VOISINS LES PLUS PROCHES. NOUS EXPOSONS ENSUITE LA SEGMENTATION NON SUPERVISEE ADAPTATIVE BASEE SUR LE CONCEPT D'ESTIMATION LOCALE. UNE ETUDE DE ROBUSTESSE DES METHODES DE SEGMENTATION A ETE ABORDEE, ELLE PERMET DE CHOISIR DES ESTIMATEURS SELON LE COMPORTEMENT DE LA METHODE DE SEGMENTATION VIS A VIS DES PARAMETRES ESTIMES. ENFIN, UNE PARTIE DE CE TRAVAIL EST CONSACREE A LA SEGMENTATION SPATIO TEMPORELLE DES SEQUENCES D'IMAGES DANS LE CAS DE LA MODELISATION PAR CHAINES DE MARKOV CACHEES. NOUS PROPOSONS TROIS ALGORITHMES DE SEGMENTATION NON SUPERVISEE QUI DIFFERENT PAR LA FACON D'EXPLOITER L'INFORMATION CONTENUE DANS LES IMAGES PRECEDENTES

Download or read book Cha nes de Markov cach es et s paration non supervis e de sources written by Selwa Rafi and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Le problème de la restauration est rencontré dans domaines très variés notamment en traitement de signal et de l'image. Il correspond à la récupération des données originales à partir de données observées. Dans le cas de données multidimensionnelles, la résolution de ce problème peut se faire par différentes approches selon la nature des données, l'opérateur de transformation et la présence ou non de bruit. Dans ce travail, nous avons traité ce problème, d'une part, dans le cas des données discrètes en présence de bruit. Dans ce cas, le problème de restauration est analogue à celui de la segmentation. Nous avons alors exploité les modélisations dites chaînes de Markov couples et triplets qui généralisent les chaînes de Markov cachées. L'intérêt de ces modèles réside en la possibilité de généraliser la méthode de calcul de la probabilité à posteriori, ce qui permet une segmentation bayésienne. Nous avons considéré ces méthodes pour des observations bi-dimensionnelles et nous avons appliqué les algorithmes pour une séparation sur des documents issus de manuscrits scannés dans lesquels les textes des deux faces d'une feuille se mélangeaient. D'autre part, nous avons attaqué le problème de la restauration dans un contexte de séparation aveugle de sources. Une méthode classique en séparation aveugle de sources, connue sous l'appellation "Analyse en Composantes Indépendantes" (ACI), nécessite l'hypothèse d'indépendance statistique des sources. Dans des situations réelles, cette hypothèse n'est pas toujours vérifiée. Par conséquent, nous avons étudié une extension du modèle ACI dans le cas où les sources peuvent être statistiquement dépendantes. Pour ce faire, nous avons introduit un processus latent qui gouverne la dépendance et/ou l'indépendance des sources. Le modèle que nous proposons combine un modèle de mélange linéaire instantané tel que celui donné par ACI et un modèle probabiliste sur les sources avec variables cachées. Dans ce cadre, nous montrons comment la technique d'Estimation Conditionnelle Itérative permet d'affaiblir l'hypothèse usuelle d'indépendance en une hypothèse d'indépendance conditionnelle.

Download or read book Quantum Mechanics Volume 3 written by Claude Cohen-Tannoudji and published by John Wiley & Sons. This book was released on 2019-12-16 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new, third volume of Cohen-Tannoudji's groundbreaking textbook covers advanced topics of quantum mechanics such as uncorrelated and correlated identical particles, the quantum theory of the electromagnetic field, absorption, emission and scattering of photons by atoms, and quantum entanglement. Written in a didactically unrivalled manner, the textbook explains the fundamental concepts in seven chapters which are elaborated in accompanying complements that provide more detailed discussions, examples and applications. * Completing the success story: the third and final volume of the quantum mechanics textbook written by 1997 Nobel laureate Claude Cohen-Tannoudji and his colleagues Bernard Diu and Franck Laloë * As easily comprehensible as possible: all steps of the physical background and its mathematical representation are spelled out explicitly * Comprehensive: in addition to the fundamentals themselves, the books comes with a wealth of elaborately explained examples and applications Claude Cohen-Tannoudji was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris where he also studied and received his PhD in 1962. In 1973 he became Professor of atomic and molecular physics at the Collège des France. His main research interests were optical pumping, quantum optics and atom-photon interactions. In 1997, Claude Cohen-Tannoudji, together with Steven Chu and William D. Phillips, was awarded the Nobel Prize in Physics for his research on laser cooling and trapping of neutral atoms. Bernard Diu was Professor at the Denis Diderot University (Paris VII). He was engaged in research at the Laboratory of Theoretical Physics and High Energy where his focus was on strong interactions physics and statistical mechanics. Franck Laloë was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris. His first assignment was with the University of Paris VI before he was appointed to the CNRS, the French National Research Center. His research was focused on optical pumping, statistical mechanics of quantum gases, musical acoustics and the foundations of quantum mechanics.

Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Download or read book Signal Processing for Communications written by Paolo Prandoni and published by Collection Savoir suisse. This book was released on 2008-06-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The treatment is therefore less focused on the mathematics and more on the conceptual aspects, the idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vein, the last chapter pulls together the individual topics as discussed throughout the book into an in-depth look at the development of an end-to-end communication system, namely, a modem for communicating digital information over an analog channel.

Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Download or read book The Physics of Information Technology written by Neil Gershenfeld and published by Cambridge University Press. This book was released on 2000-10-16 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Physics of Information Technology explores the familiar devices that we use to collect, transform, transmit, and interact with electronic information. Many such devices operate surprisingly close to very many fundamental physical limits. Understanding how such devices work, and how they can (and cannot) be improved, requires deep insight into the character of physical law as well as engineering practice. The book starts with an introduction to units, forces, and the probabilistic foundations of noise and signalling, then progresses through the electromagnetics of wired and wireless communications, and the quantum mechanics of electronic, optical, and magnetic materials, to discussions of mechanisms for computation, storage, sensing, and display. This self-contained volume will help both physical scientists and computer scientists see beyond the conventional division between hardware and software to understand the implications of physical theory for information manipulation.

Download or read book A Short Introduction to Quantum Information and Quantum Computation written by Michel Le Bellac and published by Cambridge University Press. This book was released on 2006-06-15 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum information and computation is a rapidly expanding and cross-disciplinary subject. This book, first published in 2006, gives a self-contained introduction to the field for physicists, mathematicians and computer scientists who want to know more about this exciting subject. After a step-by-step introduction to the quantum bit (qubit) and its main properties, the author presents the necessary background in quantum mechanics. The core of the subject, quantum computation, is illustrated by a detailed treatment of three quantum algorithms: Deutsch, Grover and Shor. The final chapters are devoted to the physical implementation of quantum computers, including the most recent aspects, such as superconducting qubits and quantum dots, and to a short account of quantum information. Written at a level suitable for undergraduates in physical sciences, no previous knowledge of quantum mechanics is assumed, and only elementary notions of physics are required. The book includes many short exercises, with solutions available to instructors through [email protected].

Download or read book Nonsmooth Optimization written by Claude Lemarechal and published by Elsevier. This book was released on 2014-05-19 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonsmooth Optimization contains the proceedings of a workshop on non-smooth optimization (NSO) held from March 28 to April 8,1977 in Austria under the auspices of the International Institute for Applied Systems Analysis. The papers explore the techniques and theory of NSO and cover topics ranging from systems of inequalities to smooth approximation of non-smooth functions, as well as quadratic programming and line searches. Comprised of nine chapters, this volume begins with a survey of Soviet research on subgradient optimization carried out since 1962, followed by a discussion on rates of convergence in subgradient optimization. The reader is then introduced to the method of subgradient optimization in an abstract setting and the minimal hypotheses required to ensure convergence; NSO and nonlinear programming; and bundle methods in NSO. A feasible descent algorithm for linearly constrained least squares problems is described. The book also considers sufficient minimization of piecewise-linear univariate functions before concluding with a description of the method of parametric decomposition in mathematical programming. This monograph will be of interest to mathematicians and mathematics students.

Download or read book Foundations of Signal Processing written by Martin Vetterli and published by Cambridge University Press. This book was released on 2014-09-04 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.

Download or read book Applications of Functional Analysis in Mathematical Physics written by S L (Sergeĭ Lʹvovich) 190 Sobolev and published by Hassell Street Press. This book was released on 2021-09-09 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Download or read book The Calculus of Computation written by Aaron R. Bradley and published by Springer Science & Business Media. This book was released on 2007-09-18 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written with graduate and advanced undergraduate students in mind, this textbook introduces computational logic from the foundations of first-order logic to state-of-the-art decision procedures for arithmetic, data structures, and combination theories. The textbook also presents a logical approach to engineering correct software. Verification exercises are given to develop the reader's facility in specifying and verifying software using logic. The treatment of verification concludes with an introduction to the static analysis of software, an important component of modern verification systems. The final chapter outlines courses of further study.

Download or read book Principles of Digital Communication written by Bixio Rimoldi and published by Cambridge University Press. This book was released on 2016-01-21 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive text that takes a unique top-down approach to teaching the fundamentals of digital communication for a one-semester course.

Download or read book Linear Algebra and Its Applications written by David C. Lay and published by . This book was released on 2013-07-29 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: NOTE: This edition features the same content as the traditional text in a convenient, three-hole-punched, loose-leaf version. Books a la Carte also offer a great value--this format costs significantly less than a new textbook. Before purchasing, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, including customized versions for individual schools, and registrations are not transferable. In addition, you may need a CourseID, provided by your instructor, to register for and use Pearson's MyLab & Mastering products. xxxxxxxxxxxxxxx For courses in linear algebra.This package includes MyMathLab(R). With traditional linear algebra texts, the course is relatively easy for students during the early stages as material is presented in a familiar, concrete setting. However, when abstract concepts are introduced, students often hit a wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations) are not easily understood and require time to assimilate. These concepts are fundamental to the study of linear algebra, so students' understanding of them is vital to mastering the subject. This text makes these concepts more accessible by introducing them early in a familiar, concrete "Rn" setting, developing them gradually, and returning to them throughout the text so that when they are discussed in the abstract, students are readily able to understand. Personalize learning with MyMathLabMyMathLab is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. MyMathLab includes assignable algorithmic exercises, the complete eBook, interactive figures, tools to personalize learning, and more.