METHODES MARKOVIENNES EN ESTIMATION SPECTRALE NON PARAMETRIQUE. APPLICATIONS EN IMAGERIE RADAR DOPPLER PDF Download
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Author: PHILIPPE.. CIUCIU
Publisher:
ISBN:
Category :
Languages : fr
Pages : 180
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Book Description
NOUS ETUDIONS LE PROBLEME DE L'ESTIMATION SPECTRALE DANS LA SITUATION DEFAVORABLE OU TRES PEU DE DONNEES SONT DISPONIBLES, ET NOUS L'ABORDONS SOUS L'ANGLE DE LA SYNTHESE DE FOURIER. DANS CE CADRE, L'ESTIMATION SPECTRALE S'IDENTIFIE A UN PROBLEME INVERSE LINEAIRE SOUS-DETERMINE. IL CONVIENT DE LA REGULARISER SUR LA BASE D'INFORMATIONS A PRIORI PORTANT SUR LA FORME DU SPECTRE, EN DEFINISSANT UN CRITERE COMPOSE D'UNE FONCTION DE PENALISATION ET D'UN TERME D'ATTACHE AUX DONNEES. LE MINIMISEUR GLOBAL DE CE CRITERE DEFINIT LE SPECTRE SOLUTION. CETTE FONCTION DE PENALISATION EST ASSOCIEE SPECIFIQUEMENT A CHAQUE FORME SPECTRALE ; SONT ETUDIES LES SPECTRES IMPULSIONNELS, REGULIERS, ET MELANGES, OU UN FOND CONTINU SE SUPERPOSE A UN SPECTRE DE RAIES. L'ACCENT EST MIS SUR LA CONSTRUCTION DE FONCTIONS DE PENALISATION CONVEXES D'UNE PART, CAR ELLES GARANTISSENT LE CARACTERE BIEN POSE DU PROBLEME REGULARISE ET FACILITENT LE CALCUL DE LA SOLUTION, ET CIRCULAIRES D'AUTRE PART, I.E., QUI NE DEPENDENT QUE DES MODULES DES COEFFICIENTS DE FOURIER RECHERCHES. DE PLUS, NOUS RETENONS UNE FONCTION SEPARABLE POUR ESTIMER DES RAIES, UN TERME MARKOVIEN POUR LE CAS REGULIER ET UNE ENERGIE COMPOSITE POUR LE CAS MELANGE. LE CHOIX D'UNE PENALISATION CONVEXE NOUS AMENE POUR LES CAS REGULIER ET MELANGE, A CONSIDERER UNE FONCTION NON DIFFERENTIABLE EN ZERO. LE RECOURS A UNE STRATEGIE DE NON DIFFERENTIABILITE GRADUELLE PERMET D'OBTENIR UNE SOLUTION A FAIBLE COUT CALCULATOIRE. SUR LE PLAN ALGORITHMIQUE, LA METHODE IRLS S'AVERE LA PLUS EFFICACE MAIS NE S'APPLIQUE QU'A L'ESTIMATION DE RAIES. NOUS PROPOSONS DONC DES GENERALISATIONS AUX AUTRES CAS REPOSANT SUR L'INTERPRETATION SEMI-QUADRATIQUE AUGMENTEE DE LA PENALISATION. LA METHODE DE RELAXATION PAR BLOCS RESULTANTE EST CONVERGENTE ET COMPETITIVE AVEC UN ALGORITHME DE GRADIENT PSEUDO-CONJUGUE. ENFIN, L'INTERET ET L'EFFICACITE DES METHODES DEVELOPPEES SONT ILLUSTRES SUR SIGNAUX SYNTHETIQUES ET REELS DANS LE CADRE DE L'IMAGERIE RADAR DOPPLER.
Author: PHILIPPE.. CIUCIU
Publisher:
ISBN:
Category :
Languages : fr
Pages : 180
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Book Description
NOUS ETUDIONS LE PROBLEME DE L'ESTIMATION SPECTRALE DANS LA SITUATION DEFAVORABLE OU TRES PEU DE DONNEES SONT DISPONIBLES, ET NOUS L'ABORDONS SOUS L'ANGLE DE LA SYNTHESE DE FOURIER. DANS CE CADRE, L'ESTIMATION SPECTRALE S'IDENTIFIE A UN PROBLEME INVERSE LINEAIRE SOUS-DETERMINE. IL CONVIENT DE LA REGULARISER SUR LA BASE D'INFORMATIONS A PRIORI PORTANT SUR LA FORME DU SPECTRE, EN DEFINISSANT UN CRITERE COMPOSE D'UNE FONCTION DE PENALISATION ET D'UN TERME D'ATTACHE AUX DONNEES. LE MINIMISEUR GLOBAL DE CE CRITERE DEFINIT LE SPECTRE SOLUTION. CETTE FONCTION DE PENALISATION EST ASSOCIEE SPECIFIQUEMENT A CHAQUE FORME SPECTRALE ; SONT ETUDIES LES SPECTRES IMPULSIONNELS, REGULIERS, ET MELANGES, OU UN FOND CONTINU SE SUPERPOSE A UN SPECTRE DE RAIES. L'ACCENT EST MIS SUR LA CONSTRUCTION DE FONCTIONS DE PENALISATION CONVEXES D'UNE PART, CAR ELLES GARANTISSENT LE CARACTERE BIEN POSE DU PROBLEME REGULARISE ET FACILITENT LE CALCUL DE LA SOLUTION, ET CIRCULAIRES D'AUTRE PART, I.E., QUI NE DEPENDENT QUE DES MODULES DES COEFFICIENTS DE FOURIER RECHERCHES. DE PLUS, NOUS RETENONS UNE FONCTION SEPARABLE POUR ESTIMER DES RAIES, UN TERME MARKOVIEN POUR LE CAS REGULIER ET UNE ENERGIE COMPOSITE POUR LE CAS MELANGE. LE CHOIX D'UNE PENALISATION CONVEXE NOUS AMENE POUR LES CAS REGULIER ET MELANGE, A CONSIDERER UNE FONCTION NON DIFFERENTIABLE EN ZERO. LE RECOURS A UNE STRATEGIE DE NON DIFFERENTIABILITE GRADUELLE PERMET D'OBTENIR UNE SOLUTION A FAIBLE COUT CALCULATOIRE. SUR LE PLAN ALGORITHMIQUE, LA METHODE IRLS S'AVERE LA PLUS EFFICACE MAIS NE S'APPLIQUE QU'A L'ESTIMATION DE RAIES. NOUS PROPOSONS DONC DES GENERALISATIONS AUX AUTRES CAS REPOSANT SUR L'INTERPRETATION SEMI-QUADRATIQUE AUGMENTEE DE LA PENALISATION. LA METHODE DE RELAXATION PAR BLOCS RESULTANTE EST CONVERGENTE ET COMPETITIVE AVEC UN ALGORITHME DE GRADIENT PSEUDO-CONJUGUE. ENFIN, L'INTERET ET L'EFFICACITE DES METHODES DEVELOPPEES SONT ILLUSTRES SUR SIGNAUX SYNTHETIQUES ET REELS DANS LE CADRE DE L'IMAGERIE RADAR DOPPLER.
Author: Zoltan Kato
Publisher: Now Pub
ISBN: 9781601985880
Category : Computers
Languages : en
Pages : 168
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Book Description
Markov Random Fields in Image Segmentation provides an introduction to the fundamentals of Markovian modeling in image segmentation as well as a brief overview of recent advances in the field. Segmentation is formulated within an image labeling framework, where the problem is reduced to assigning labels to pixels. In a probabilistic approach, label dependencies are modeled by Markov random fields (MRF) and an optimal labeling is determined by Bayesian estimation, in particular maximum a posteriori (MAP) estimation. The main advantage of MRF models is that prior information can be imposed locally through clique potentials. MRF models usually yield a non-convex energy function. The minimization of this function is crucial in order to find the most likely segmentation according to the MRF model. Classical optimization algorithms including simulated annealing and deterministic relaxation are treated along with more recent graph cut-based algorithms. The primary goal of this monograph is to demonstrate the basic steps to construct an easily applicable MRF segmentation model and further develop its multi-scale and hierarchical implementations as well as their combination in a multilayer model. Representative examples from remote sensing and biological imaging are analyzed in full detail to illustrate the applicability of these MRF models. Furthermore, a sample implementation of the most important segmentation algorithms is available as supplementary software. Markov Random Fields in Image Segmentation is an invaluable resource for every student, engineer, or researcher dealing with Markovian modeling for image segmentation.
Author: Vladimir I︠A︡kovlevich Katkovnik
Publisher: SPIE-International Society for Optical Engineering
ISBN:
Category : Computers
Languages : en
Pages : 584
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Book Description
This book deals with a wide class of novel and efficient adaptive signal processing techniques developed to restore signals from noisy and degraded observations. These signals include those acquired from still or video cameras, electron microscopes, radar, X-rays, or ultrasound devices, and are used for various purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific. In many cases useful information and high quality must be extracted from the imaging. However, often raw signals are not directly suitable for this purpose and must be processed in some way. Such processing is called signal reconstruction. This book is devoted to a recent and original approach to signal reconstruction based on combining two independent ideas: local polynomial approximation and the intersection of confidence interval rule.
Author: Claude Lemarechal
Publisher: Elsevier
ISBN: 1483188760
Category : Technology & Engineering
Languages : en
Pages : 195
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Book Description
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.
Author: Zhu, Ce
Publisher: IGI Global
ISBN: 1616928336
Category : Computers
Languages : en
Pages : 502
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Book Description
"This book spans a number of interdependent and emerging topics in streaming media, offering a comprehensive collection of topics including media coding, wireless/mobile video, P2P media streaming, and applications of streaming media"--Provided by publisher.
Author: S L (Sergeĭ Lʹvovich) 190 Sobolev
Publisher: Hassell Street Press
ISBN: 9781013706981
Category :
Languages : en
Pages : 256
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Book Description
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.
Author: Eliot W. Zimmerman
Publisher:
ISBN:
Category : Forest fire detection
Languages : en
Pages : 36
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Book Description
Author: Thierry Dutoit
Publisher: Springer Science & Business Media
ISBN: 0387745351
Category : Technology & Engineering
Languages : en
Pages : 456
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Book Description
Applied Signal Processing: A MATLAB-Based Proof of Concept benefits readers by including the teaching background of experts in various applied signal processing fields and presenting them in a project-oriented framework. Unlike many other MATLAB-based textbooks which only use MATLAB to illustrate theoretical aspects, this book provides fully commented MATLAB code for working proofs-of-concept. The MATLAB code provided on the accompanying online files is the very heart of the material. In addition each chapter offers a functional introduction to the theory required to understand the code as well as a formatted presentation of the contents and outputs of the MATLAB code. Each chapter exposes how digital signal processing is applied for solving a real engineering problem used in a consumer product. The chapters are organized with a description of the problem in its applicative context and a functional review of the theory related to its solution appearing first. Equations are only used for a precise description of the problem and its final solutions. Then a step-by-step MATLAB-based proof of concept, with full code, graphs, and comments follows. The solutions are simple enough for readers with general signal processing background to understand and they use state-of-the-art signal processing principles. Applied Signal Processing: A MATLAB-Based Proof of Concept is an ideal companion for most signal processing course books. It can be used for preparing student labs and projects.
Author: Michael Kipp
Publisher: Springer Science & Business Media
ISBN: 3642047920
Category : Computers
Languages : en
Pages : 231
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Book Description
Based on the International Workshop on "Multimodal Corpora: From Models of Natural Interaction to Systems and Applications", this expanded collection presents a comprehensive review of the current research in the field.
Author: Dimitros Tzovaras
Publisher: Springer Science & Business Media
ISBN: 3540783458
Category : Technology & Engineering
Languages : en
Pages : 321
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Book Description
tionship indicates how multimodal medical image processing can be unified to a large extent, e. g. multi-channel segmentation and image registration, and extend information theoretic registration to other features than image intensities. The framework is not at all restricted to medical images though and this is illustrated by applying it to multimedia sequences as well. In Chapter 4, the main results from the developments in plastic UIs and mul- modal UIs are brought together using a theoretic and conceptual perspective as a unifying approach. It is aimed at defining models useful to support UI plasticity by relying on multimodality, at introducing and discussing basic principles that can drive the development of such UIs, and at describing some techniques as proof-of-concept of the aforementioned models and principles. In Chapter 4, the authors introduce running examples that serve as illustration throughout the d- cussion of the use of multimodality to support plasticity.
