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Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB (R).
・ISBN 978-1-4822-5335-1 paper GB£ 109.99
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| 著者・編者 | Poularikas, Alexander D., |
|---|---|
| 出版社 | (CRC Press Inc, US) |
| 出版年月 | 2014 |
| ページ数 | 364 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-54931＞ |
解説
Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB (R) covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area-the least mean square (LMS) adaptive filter.
This largely self-contained text:
- Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions
- Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces
- Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton's algorithm
- Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples
- Delivers a concise introduction to MATLAB (R), supplying problems, computer experiments, and more than 110 functions and script files
Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB (R) clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems.