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