Signal Analysis  Wavelets, Filter Banks, Time-Frequency Transforms and Applications, English (revised edition) Cover

Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications, English (revised edition)

ISBN/ASIN: 9780471986263,9780470841839 | 1999 | English | pdf | 327/327 pages | 5.12 Mb
Author: Alfred Mertins(auth.)

Signal analysis gives an insight into the properties of signals and stochastic processes by methodology. Linear transforms are integral to the continuing growth of signal processes as they characterize and classify signals. In particular, those transforms that provide time-frequency signal analysis are attracting greater numbers of researchers and are becoming an area of considerable importance. The key characteristic of these transforms, along with a certain time-frequency localization called the wavelet transform and various types of multirate filter banks, is their high computational efficiency. It is this computational efficiently which accounts for their increased application. This book provides a complete overview and introduction to signal analysis. It presents classical and modern signal analysis methods in a sequential structure starting with the background to signal theory. Progressing through the book the author introduces more advanced topics in an easy to understand style. Including recent and emerging topics such as filter banks with perfect reconstruction, time frequency and wavelets. With great accuracy and technical merit, this book makes a useful and original contribution to the current literature.Content:
Chapter 1 Signals and Signal Spaces (pages 1–21):
Chapter 2 Integral Signal Representations (pages 22–46):
Chapter 3 Discrete Signal Representations (pages 47–74):
Chapter 4 Examples of Discrete Transforms (pages 75–100):
Chapter 5 Transforms and Filters for Stochastic Processes (pages 101–142):
Chapter 6 Filter Banks (pages 143–195):
Chapter 7 Short?Time Fourier Analysis (pages 196–209):
Chapter 8 Wavelet Transform (pages 210–264):
Chapter 9 Non?Linear Time?Frequency Distributions (pages 265–298):

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