Wavelets and Multiscale Signal Processing (Applied Mathematics and Mathematical Computation)

Albert Cohen

ISBN 10: 0412575906 / ISBN 13: 9780412575907

Published by Chapman and Hall/CRC, 1995

About this Item

238 pages. 9.00x5.75x0.75 inches. In Stock.

Seller Inventory # __0412575906

Bibliographic Details

• Title: Wavelets and Multiscale Signal Processing (Applied Mathematics and Mathematical Computation)
• Publisher: Chapman and Hall/CRC
• Publication Date: 1995
• Language: English
• ISBN 10: 0412575906
• ISBN 13: 9780412575907
• Binding: Hardcover
• Condition: Brand New

About this title

Synopsis

Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing.
Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for the algorithms are the subjects of Chapter 3. Chapter 5 looks at multiscale decomposition as it applies to stochastic processing, in particular to signal and image processing.

From the Back Cover

This book is based on Ondelettes et Traitement Numerique du Signal by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters, and the importance of regularity for the algorithms are the subjects of Chapter 3. Chapter 5 looks at multiscale decomposition as it applies to stochastic processing, in particular to signal and image processing. Wavelets and Multiscale Signal Processing will be of particular interest to mathematicians working in analysis, academic and industrial electrical engineers, and researchers who need to analyse time series, in areas such as hydrodynamics, aeronautics, meteorology, geophysics, statistics and economics.