Title :
Automatic classification of underwater sonar signals
Author :
Hashem, Hassan Fahmy
Author_Institution :
Alexandria High Inst. of Technol.
Abstract :
Much work has been performed recently in the area of automatic recognition of the sonar signals to reduce the operator load when confronted with many beams of data concurrently. In this paper we applied and compared between different feature extraction methods such as wavelet basis method, discrete cosine transform method (DCT) and linear prediction method (LP) and then we applied neural network techniques to the processing of sonar signals classification
Keywords :
discrete cosine transforms; feature extraction; geophysical signal processing; neural nets; oceanographic techniques; signal classification; sonar signal processing; wavelet transforms; automatic signal classification; automatic wavelet selection; discrete cosine transform method; feature extraction; linear prediction method; neural network; operator load; sonar signal processing; wavelet basis method; Artificial neural networks; Discrete cosine transforms; Discrete wavelet transforms; Neural networks; Pattern classification; Predictive models; Sonar applications; Target recognition; Vectors; Wavelet transforms;
Conference_Titel :
OCEANS '04. MTTS/IEEE TECHNO-OCEAN '04
Conference_Location :
Kobe
Print_ISBN :
0-7803-8669-8
DOI :
10.1109/OCEANS.2004.1405753
