Synopses & Reviews
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.
Synopsis
The analysis of non-stationary signals requires tools that, unlike traditional methods, yield information about the time localization of a given frequency component. Time-frequency representations have been used successfully for these purposes in many applications, such as speech, radar and sonar, image, and biological signal processing. This book investigates the use of various time-frequency representations, describes the advantages of one representation over another for particular applications, and provides pseudo-code of the computational algorithms for these representations so that readers can apply them to their own specific problems.
-- Includes an introduction designed as a tutorial for those not well versed in time-frequency representations
-- Presents applications of time-frequency representations explaining main concepts without extensive theoretical proofs
-- Provides MATLAB or pseudo-code with flow graphs explaining algorithm implementation for the practicing engineer
-- Contains many illustrated examples that demonstrate the use of time-frequency representations
Table of Contents
Time-frequency processing : tutorial on principles and practice / Antonia Papandreou-Suppappola -- Interference excision via time-frequency distributions / Alan R. Lindsey, Liang Zhao and Moeness Amin -- Positive time-frequency distributions / Patrick Loughlin and Leon Cohen -- Positive time-frequency distributions and acoustic echoes / Dale Groutage ... et al. -- Time-frequency reassignment : from principles to algorithms / Patrick Flandrin, F. Auger and E. Chassande-Mottin -- Linear time-frequency filters : on-line algorithms and applications / Gerald Matz and Franz Hlawatsch -- Discrete reduced inteference sic distributions / William J. Williams -- Time-frequency analysis of seismic reflection data / Philippe Steeghs, Richard G. Baraniuk and Jan Erik Odegard -- Time-frequency methodology for newborn EEG seizure detection / Boualem Boashash and Mostefa Mesbah -- Quadratic time-frequency features for speech recognition / James Droppo and Les Atlas.