DocumentCode :
2491292
Title :
Adaptive wavelets classification of transient sonar signals
Author :
Jingyuan, Zhang ; Xingzhou, Jiang ; Bingcheng, Yuan
Author_Institution :
Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
2
fYear :
1996
fDate :
14-18 Oct 1996
Firstpage :
1535
Abstract :
This paper discusses the applicability of adaptive wavelets for the classification of transient sonar signals. A two-step classification method is presented. The first step is the extraction of adaptive wavelet features. The second step is the signal classification using a feedforward neural network. Four classes of transient sonar signals are used for an experiment. The test result shows that the performance of adaptive wavelets for this application is rather better than that of the power spectral features based classifier
Keywords :
adaptive signal processing; electrical engineering; electrical engineering computing; feature extraction; feedforward neural nets; sonar signal processing; transient analysis; wavelet transforms; adaptive wavelet feature extraction; adaptive wavelets classification; experiment; feedforward neural network; performance; power spectral features based classifier; signal classification; transient sonar signals; two-step classification method; Computer networks; Feature extraction; Feedforward systems; Function approximation; Hidden Markov models; Neural networks; Pattern classification; Roads; Sonar; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
Type :
conf
DOI :
10.1109/ICSIGP.1996.571172
Filename :
571172
Link To Document :
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