Discrete stochastic processes and optimal filtering /
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 pro...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
London, U.K. : Hoboken, N.J. :
ISTE ; John Wiley,
2010.
|
| Edition: | 2nd ed. |
| Series: | Digital signal and image processing series.
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| 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. |
|---|---|
| Item Description: | Translated from French. |
| Physical Description: | 1 online resource (xii, 287 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781118600481 1118600487 9781118600351 1118600355 9781118600535 1118600533 |