Title :
Detection and classification of multicomponent signals
Author :
Fineberg, A.B. ; Mammone, R.J.
Author_Institution :
CAIP Center, Rutgers Univ., Piscataway, NJ, USA
Abstract :
The multicomponent nature of many naturally occurring signals, such as speech, is exploited to provide a new means of detection and classification. A component of a multicomponent signal is defined in terms of the local bandwidth about the instantaneous frequency in the time-frequency distribution. The components are isolated by an adaptive partitioning algorithm which is constrained to overcome the interference terms often present in such distributions. The redundancy which may be present in the individual components of the signal is discussed along with the means to detect and classify the signal based upon this redundancy. The application of this approach to a vowel classification task using the spectrogram is presented and is shown to provide performance which is favorable compared to that obtained with conventional methods
Keywords :
frequency-domain analysis; signal detection; speech analysis and processing; time-domain analysis; adaptive partitioning algorithm; constrained algorithm; instantaneous frequency; interference terms; local bandwidth; multicomponent signals; signal classification; signal detection; spectrogram; speech; time-frequency distribution; vowel classification; Bandwidth; Humans; Multiple signal classification; Redundancy; Signal generators; Signal processing; Signal representations; Spectrogram; Speech; Time frequency analysis;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186615