Wavelets, approximation, and statistical applications /
The mathematical theory of wavelets was developed by Yes Meyer and many collaborators about ten years ago. It was designed for approximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, and image and signal processing. Five years...
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| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
1998.
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| Series: | Lecture notes in statistics (Springer-Verlag) ;
v. 129. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | The mathematical theory of wavelets was developed by Yes Meyer and many collaborators about ten years ago. It was designed for approximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, and image and signal processing. Five years ago wavelet theory progressively appeared to be a powerful framework for nonparametric statistical problems. Efficient computation implementations are beginning to surface in the nineties. This book brings toghether these three streams of wavelet theory and introduces the novice in this field to these aspects. Readers interested in the theory and construction of wavelets will find in a condensed form results that are scattered in the research literature. A practitioner will be able to use wavelets via the available software code. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xviii, 265 pages) : illustrations. |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages 248-259) and indexes. |
| ISBN: | 9781461222224 (electronic bk.) 1461222222 (electronic bk.) |