Because most real-world signals, including speech, sonar, communication, and biological signals, are non-stationary, traditional signal analysis tools such as Fourier transforms are of limited use because they do not provide easily accessible information about the localization of a given frequency component. A more suitable approach for those studying non-stationary signals is the use of time frequency representations that are functions of both time and frequency.
Applications in Time-Frequency Signal Processing investigates the use of various time-frequency representations, such as the Wigner distribution and the spectrogram, in diverse application areas. Other books tend to focus on theoretical development. This book differs by highlighting particular applications of time-frequency representations and demonstrating how to use them. It also provides pseudo-code of the computational algorithms for these representations so that you can apply them to your own specific problems.
Written by leaders in the field, this book offers the opportunity to learn from experts. Time-Frequency Representation (TFR) algorithms are simplified, enabling you to understand the complex theories behind TFRs and easily implement them. The numerous examples and figures, review of concepts, and extensive references allow for easy learning and application of the various time-frequency representations.
Table of Contents
Time-Frequency Processing: A Tutorial on Principles and Practice, Antonia Papendreou-Suppappol
Inference Excision via Time-Frequency Distributions: Alan R. Lindsey, Liang Zhao, Moeness Amin
Positive Time-Frequency Distributions, Patrick Loughlin, Leon Cohen
Positive Time-Frequency Distributions and Acoustic Echoes, Dale Groutage, David Bennink, Patrick Loughlin, Leon Cohen
Time-Frequency Reassignment: From Principles to Algorithms, P. Flandrin, F. Auger, E. Chassande-Mottin
Linear Time-Frequency Filters: Online Algorithms and Applications, Gerald Matz, Franz Hlawatsch
Discrete Reduced Interference Distributions, William J. Williams
Time-Frequency Analysis of Seismic Reflection Data, Phillippe Steeghs, Richard Baraniuk, Jan Erik Odegard
Time-Frequency Methodology for Newborn EEG Seizure Detection, Boualem Boashash, Mostefa Mesbah
Quadratic Time-Frequency Features for Speech Recognition, James Droppo, Les Atlas
"This book is a reference for applications involving signals with time-varying spectra reference. Written by leaders in the field, it offers an opportunity to learn from experts. Numerous examples and figures, a review of concepts, and simplified TFR algorithms assist the understanding of complex theories behind TFRs and their implementation."
- IEEE Signal Processing Magazine