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Title:
Discrete stochastic processes and optimal filtering
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Publication Information:
London : ISTE, 2007
ISBN:
9781905209743
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30000010159361 TK5102.9 B474 2007 Open Access Book Book
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30000003495847 TK5102.9 B474 2007 Open Access Book Book
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Summary

Summary

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using Matlab.


Author Notes

Jean-Claude Bertein has a Master's and PhD degree from the University of Paris VI. He was formerly a research engineer at Alcatel and today is Professor in the Department of Mathematics and Physics at the Graduate School of Electrical and Electronic Engineering (ESIEE) Paris.

Roger Ceschi is an ENSEA engineer and holds a Master's and PhD degree from the University of Paris XI. He was formerly Director of the ENSEA and today he is Director General of the ESIEE Amiens. He is also the author of a theorem on analytic signals and is Visiting Professor at the BIPT and BIT Universities in China.


Table of Contents

Preface
Introduction
Chapter 1 Random vectors
Chapter 2 Gaussian vectors
Chapter 3 Introduction to discrete time processes
Chapter 4 Estimation
Chapter 5 The Wiener filter
Chapter 6 Adaptive filtering: algorithms of the gradient and the LMS
Chapter 7 The Kalman filter
Table of Symbols and Notations
Bibliography
Index
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