| Description |
1 online resource (xx, 459 pages) : illustrations |
| Contents |
1. Introduction -- pt. I. Statistical foundations -- 2. NonGaussian models -- 3. Order statistics -- 4. Statistical foundations of filtering -- pt. II. Signal processing with order statistics -- 5. Median and weighted median smoothers -- 6. Weighted median filters -- 7. Linear combination of order statistics -- pt. III. Signal processing with the stable model -- 8. Myriad smoothers -- 9. Weighted myriad filters |
| Summary |
Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which emerge from statistical estimation principles, and where the underlying signals are non-Gaussian, rather than Gaussian, processes. Notably, by concentrating on just two non-Gaussian models, a large set of tools is developed that encompass a large portion of the nonlinear signal processing tools proposed in the literature over the past several decades. Key features include:* Numerous problems at the end of each chapter to aid development |
| Analysis |
Communication Technology |
| Bibliography |
Includes bibliographical references (pages 365-379) and index |
| Notes |
English |
|
Print version record |
| Subject |
Signal processing -- Mathematics
|
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Statistics.
|
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statistics.
|
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COMPUTERS -- Information Theory.
|
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TECHNOLOGY & ENGINEERING -- Signals & Signal Processing.
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Signal processing -- Mathematics
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Statistics
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| Genre/Form |
Electronic books
|
| Form |
Electronic book
|
| ISBN |
0471691844 |
|
9780471691846 |
|
0471676241 |
|
9780471676249 |
|
0471691852 |
|
9780471691853 |
|
1280272937 |
|
9781280272936 |
|
9786610272938 |
|
661027293X |
|
0470323612 |
|
9780470323618 |
|
