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Discrete stochastic processes and optimal filtering

This title is concerned with the founding principles of optimal filters. It proposes several reminders about both random vectors and Gaussian vectors. The study of discrete time processes makes it possible to tackle digital filtering; a chapter on estimation gives the principle results necessary for...

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Bibliographic Details
Main Authors: Bertein, Jean-Claude
Corporate Authors: Wiley InterScience Online service
Group Author: Ceschi, Roger
Published:
Literature type: Electronic eBook
Language: English
French
Subjects:
Signal processing > Mathematics
Digital filters Mathematics
Stochastic processes
Traitement du signal > Mathématiques
Filtres numériques Mathématiques
Processus stochastiques
COMPUTERS > Information Theory
TECHNOLOGY & ENGINEERING > Signals & Signal Processing
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9780470612293
Summary: This title is concerned with the founding principles of optimal filters. It proposes several reminders about both random vectors and Gaussian vectors. The study of discrete time processes makes it possible to tackle digital filtering; a chapter on estimation gives the principle results necessary for the construction of the Wiener filter and of the adaptive filter used in the case of stationary signals. It concludes with an examination of Kalman filtering which extends optimal filtering to the case of non-stationary signals. Exercises with solutions punctuate each chapter and practical exampl
Item Description: "First published in France in 2005 by Hermes Science/Lavoisier entitled "Processus stochastiques discrets et filtrages optimaux"."
Carrier Form: ix, 287 p. : ill. ; 24 cm.
Bibliography: Includes bibliographical references (p. [283]) and index.
ISBN: 9780470612293
0470612290
9781847046246 (electronic bk.)
184704624X (electronic bk.)
1280847859
9781280847851
Index Number: TK5102
CLC: TN911.72
Contents: Cover -- Table of Contents -- Preface -- Introduction -- Chapter 146; Random Vectors -- 146;146; Definitions and general properties -- 146;246; Spaces L140;dP41; and L240;dP41; -- 146;346; Mathematical expectation and applications -- 146;446; Second order random variables and vectors -- 146;546; Linear independence of vectors of L240;dP41; -- 146;646; Conditional expectation 40;concerning random vectors with -- 146;746; Exercises for Chapter 1 -- Chapter 246; Gaussian Vectors -- 246;146; Some reminders regarding random Gaussian vectors -- 246;246; Definition and characterization of Gaussian

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