| Description |
1 online resource (xviii, 343 pages) : illustrations |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Chapter 1. Vectors -- chapter 2. Matrices -- chapter 3. Processing of discrete deterministic signals : discrete systems -- chapter 4. Discrete-time random processes -- chapter 5. The Wiener filter -- chapter 6. Eigenvalues of Rx : properties of the error surface -- chapter 7. Newton's and steepest descent methods -- chapter 8. The least mean-square algorithm -- chapter 9. Variants of least mean-square algorithm. |
| Summary |
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® 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 distributionsExplains how to find the eigenvalues and eigenvectors of a. |
| Language |
English. |
| Subject |
MATLAB.
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MATLAB |
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Adaptive filters -- Mathematical models.
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Adaptive signal processing -- Mathematics.
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Least squares -- Data processing.
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Filtres adaptatifs -- Modèles mathématiques. |
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Traitement adaptatif du signal -- Mathématiques. |
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Adaptive filters -- Mathematical models |
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Adaptive signal processing -- Mathematics |
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Least squares -- Data processing |
| Other Form: |
Print version: Poularikas, Alexander D., 1933- Adaptive filtering. Boca Raton : Taylor & Francis, 2014 9781482253351 (DLC) 2014027999 (OCoLC)884440184 |
| ISBN |
9781482253368 (electronic bk.) |
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1482253364 (electronic bk.) |
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(paperback) |
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(paperback) |
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