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.

Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insight into how to use TFSAP methods to develop the engineering application systems they are looking to implement.
A comprehensive tutorial introduction to Time-Frequency Signal Analysis and Processing TFSAP, accessible to anyone who has taken a first course in signals and systems;

Key theory and algorithms, concisely presented by some of the leading authorities on the respective topics

Applications, written by leading researchers, showing how to use TFSAP methods to develop

Availability of a software package on TFSAP which consists of the most important algorithms described in the book so that they are ready for use with an easy GUi (Graphic User Interface). New sections on Efficient Fast Algorithms and a section "Getting Started" which allows users to start using the algorithms on simulated and real examples, compare the results presented in the book and then insert the algorithms in their own application and adapt as needed (Source code is provided)

Two new chapters, 23 new sections, all sections include the latest references.

New topics in this edition include: Efficient algorithms (with source code), the EMD, the S transform, time-frequency modelling, more mathematical foundations, relationship between QTFDs and Wavelet Transforms; new advanced applications such as cognitive radio; watermarking; noise reduction in the time-frequency domain; a time-frequency approach for spike detection; algorithms for Time-Frequency Image Processing; a full new chapter dedicated to Time-Frequency applications in neuroscience; a practical new chapter to help new users get started.