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Chapter 1 gives an overview of the topics covered and introduces the concept of multiresolution that is central in both theory and applications. Chapter 2 is a review of fundamentals that makes the book self-contained, and it includes discussions of vector spaces, Fourier theory, signal processing and time-frequency analysis.

Chapter 3 develops discrete-time linear expansions based on filter banks or subband coding. The two-channel case is studied in detail. The multichannel case as well as transmultiplexers are developed and design examples are given.

Theory of Subband Decomposition

Chapter 4 develops wavelets, both with direct approaches and based on filter banks, and describes wavelet series and their computation, as well as the construction of modified local Fourier transforms. Chapter 5 discusses continuous wavelet and local Fourier transforms that are used in signal analysis, as well as discretized versions leading to frames. Chapter 6 addresses efficient algorithms for filter banks and wavelet computations.

Chapter 7 concludes coverage by describing signal compression where filter banks and wavelets play important roles, including speech, audio, image and video compression.

Source coding using transforms, quantization, and entropy coding are studied in detail, and the usefulness of multiresolution coding in current applications is discussed. In addition, each chapter includes numerous illustrative examples and several appendices cover additional material.

The book includes about a hundred homework problems, and contains illustrations and photographs. Convert currency.

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This book presents a unified view of wavelets and subband coding with a signal processing perspective. Covers the discrete-time case, development of wavelets, continuous wavelet and local Fourier transforms, efficient algorithms for computations, and signal compression. Home page url. Wavelets, their friends, and what they can do for you by M.

Sub-Band Coding - Discrete Time Signal Processing

Pereyra, M. Mohlenkamp - Ohio University We present an introduction to the theory of wavelets with an emphasis in applications.


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