Discrete Stochastic Processes and Optimal Filtering

✍ Scribed by Jean-Claude Bertein, Roger Ceschi

Publisher: Wiley-ISTE
Year: 2007
Tongue: English
Leaves: 301
Series: Digital Signal & Image Processing Series (ISTE-DSP)
Edition: illustrated edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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

Discrete Stochastic Processes and Optimal Filtering......Page 1
Contents......Page 7
Preface......Page 11
Introduction......Page 13
1. Random Vectors......Page 15
2. Gaussian Vectors......Page 77
3. Introduction to Discrete Time Processes......Page 107
4. Estimation......Page 155
5. The Wiener Filter......Page 195
6. Adaptive Filtering: Algorithm of the Gradient and the LMS......Page 211
7. The Kalman Filter......Page 251
Symbols and Notations......Page 295
Bibliography......Page 297
Index......Page 299

✦ Subjects

Приборостроение;Обработка сигналов;

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