Time-Frequency Based Feature Extraction and Classification: Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches

In many fields such as telecommunications, multimedia, medical technology, radar and sonar, man-machine communications, we utilize advanced signal processing techniques to extrapolate underlying information on specific problems for the purpose of decision making. Traditional signal processing approaches assume the stationarity of signals, which in practice is not often satisfied. Hence, time or frequency descriptions alone are insufficient to provide comprehensive information about such signals. On the contrary, time-frequency analysis is more suitable for non-stationary signals. Therefore, this book provides a status report of feature-based signal processing in the time-frequency domain through an overview of recent contributions. The feature considered here is energy concentration. The material covered in this book should help shed some light on this exciting topic, and should be especially useful to professionals in many fields dealing with the analysis of non-stationary signals.

Dr. Ervin Sejdić is with the University of Toronto, Toronto, Ontario, Canada. Dr. Igor Djurović is with the University of Montenegro, Podgorica, Montenegro. Dr. Jin Jiang is with the University of Western Ontario, London, Ontario, Canada. Dr. LJubiša Stanković is with the University of Montenegro, Podgorica, Montenegro.