Title :
An efficient method of target classification
Author :
Zhang, Yanning ; Licheng Jiao ; Songhua, Hu
Author_Institution :
Key Lab. for Radar Signal Process., Xidian Univ., Xi´´an, China
Abstract :
The People´s Republic of China´s fishery and offshore petroleum development industries have been in urgent need of a classifier of noise signals. In this paper, a local adaptive wavelet neural network is proposed, and an efficient engineering classifier based on the local adaptive wavelet neural network is designed and applied to classifying actual ship noises. The classification experiment results are encouraging, which shows that the classifier above is an efficient engineering classifier for actual ship noises
Keywords :
acoustic noise; acoustic signal processing; aquaculture; neural nets; petroleum industry; ships; signal classification; underwater sound; wavelet transforms; People´s Republic of China; actual ship noise; fishery development; local adaptive wavelet neural network; noise signal classification; offshore petroleum development; target classification; Acoustic noise; Adaptive systems; Aquaculture; Equations; Feature extraction; Marine vehicles; Neural networks; Neurons; Radar; Wavelet transforms;
Conference_Titel :
Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4325-5
DOI :
10.1109/ICOSP.1998.770828