Discrete Stochastic Processes and Optimal Filtering

by Jean-Claude Bertein (Graduate School of Electrical and Electronic Engineering (ESIEE) Paris); Roger Ceschi (University of Paris XI, France)

• ISBN13: 9780470394939
• ISBN10: 0470394935
• Format: eBook
• Copyright: 2010-01-01
• Publisher: Wiley-ISTE

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.

Table of Contents

Preface

Introduction

Random vectors

Gaussian vectors

Introduction to discrete time processes

Estimation

The Wiener filter

Adaptive filtering: algorithms of the gradient and the LMS

The Kalman filter

Table of Symbols and Notations

Bibliography

Index

Table of Contents provided by Publisher. All Rights Reserved.