Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
โ Scribed by Ali N. Akansu, Paul R. Haddad
- Publisher
- Academic Press
- Year
- 2000
- Tongue
- English
- Leaves
- 516
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers such "hot" areas as signal compression and coding, including particular decomposition techniques and tables listing coefficients of subband and wavelet filters and other important properties. The field of this book (Electrical Engineering/Computer Science) is currently booming, which is, of course, evident from the sales of the previous edition. Since the first edition came out there has been much development, especially as far as the applications. Thus, the second edition addresses new developments in applications-related chapters, especially in chapter 4 "Filterbrook Families: Design and Performance," which is greatly expanded. * Unified and coherent treatment of orthogonal transforms, subbands, and wavelets * Coverage of emerging applications of orthogonal transforms in digital communications and multimedia * Duality between analysis and synthesis filter banks for spectral decomposition and synthesis and analysis transmultiplexer structures * Time-frequency focus on orthogonal decomposition techniques with applications to FDMA, TDMA, and CDMA
๐ SIMILAR VOLUMES
This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will
The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers suc