DocumentCode
2953188
Title
Automatic classification of underwater sonar signals
Author
Hashem, Hassan Fahmy
Author_Institution
Alexandria High Inst. of Technol., Egypt
fYear
2004
fDate
23-25 Sept. 2004
Firstpage
121
Lastpage
125
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 different feature extraction methods such as the 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 signal classification.
Keywords
discrete cosine transforms; feature extraction; neural nets; prediction theory; signal classification; sonar signal processing; wavelet transforms; DCT; LP; automatic classification; automatic recognition; discrete cosine transform method; feature extraction methods; linear prediction method; neural network; operator load; sonar signal classification; underwater sonar signals; wavelet basis method; Artificial neural networks; Discrete cosine transforms; Discrete wavelet transforms; Feature extraction; Neural networks; Pattern classification; Prediction methods; Shape; Signal processing; Sonar applications;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering, 2004. NEUREL 2004. 2004 7th Seminar on
Print_ISBN
0-7803-8547-0
Type
conf
DOI
10.1109/NEUREL.2004.1416552
Filename
1416552
Link To Document