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Multiresolution Signal Decomposition : Transforms, Subbands, and Wavelets

Name: Multiresolution Signal Decomposition : Transforms, Subbands, and Wavelets
Author: Ali N. Akansu, Richard A. Haddad, Paul R. Haddad
ISBN: 9780120471416

by Ali N. Akansu, Richard A. Haddad, Paul R. Haddad

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Overview

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

Audience: This book is intended for graduate students and R&D practitioners engaged in signal processing applications in voice and image processing, multimedia, and telecommunications. It assumes a background in linear systems and Fourier analysis, some linear algebra, random signals, and an introductory course in digital signal processing.

About the Author, Ali N. Akansu, Richard A. Haddad, Paul R. Haddad

Ali N. Akansu received the BS degree from the Technical University of Istanbul, Turkey, in 1980, the MS and Ph.D degrees from the Polytechnic University,Brooklyn, New York in 1983 and 1987, respectively, all in Electrical Engineering. He has been with the Electrical & Computer Engineering Department of the New Jersey Institute of Technology since 1987. He was an academic visitor at IBM T.J.Watson Research Center and at GEC-Marconi Electronic Systems Corp. during the summers of 1989 and 1996, and 1992, respectively. He serves as a consultantto the industry. His current research interests are signal theory, linear transform theory (subbands and wavelets) and algorithms, image-video compression andmultimedia networks, signal processing techniques for digital communications, communication networks and Internet technologies.

Richard A. Haddad received the B.E.E, M.E.E, and Ph.D. degrees in 1956, 1958, and 1962 respectively from the Polytechnic Institute of Brooklyn.He had been on the Electrical Engineering Faculty of Polytechnic University from 1961 to 1995. During his tenure there, he had served in variouscapacities. From 1981 to 1987, he was Associate Dean and then Director of the Westchester Graduate Center. During leaves of absence, he hasserved as a Member of the Technical Staff at Bell Telephone Laboratories, Whippany, N.J. and as first Director of the Engineering Division at theInstitut National d'Electricite et d'Electronique, Boumerdes, Algeria. He has also lectured and consulted in signal processing at universities in Italy,People's Republic of China. Presently he is Professor and Chair, Department of Electrical and Computer Engineering, New Jersey Institute of Technology. New Jersey.He is a senior memeber of IEEE and also an elected member of Eta Kappa Nu, Tau Beta Pi, and Sigma Xi, and the New York Academy of Sciences.

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This second edition describes objective performance criteria to measure signal compression and coding and the time-frequency properties of signals and decompositions techniques, with an overall focus on orthonormal decompositions. The chapters cover orthogonal transforms; the theory of perfect reconstruction, orthonormal two-band and M-band filter; specific filter banks and their objective performance; joint time-frequency properties of signals and the localization features of decomposition tools; basic theory of orthonormal and biorthogonal wavelet transfers and their connection to the orthonormal dyadic subband tree; and recent applications in image coding and communications applications. Graduate students and researchers who know linear system theory and Fourier analysis and are acquainted with linear algebra, random signals and processes and digital signal processing will be the text's audience. Annotation c. Book News, Inc., Portland, OR (booknews.com)