Time-Frequency Based Feature Extraction and Classification
Considering Energy Concentration as a Feature Using the Stockwell Transform and Related Approaches
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- Autoren: Ervin Sejdi , Igor Djurovi , Jin Jiang
- 2009, 260 Seiten, Maße: 15 x 22 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller
- ISBN-10: 3639219600
- ISBN-13: 9783639219609
Sprache:
Englisch
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