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According to the symmetric characteristics of bispectrum, a novel feature extraction scheme, which includes the summation-at-every-column feature vector, the summation-at-every-row feature vector and their combination in a triangle area, one of the 12 symmetric areas of bispectrum, is proposed. By using One-against-One (OAO) method of multi classification of Support Vector Machine (SVM), the mean classification accuracy for the radiated noise of underwater targets in three types is steadily above 98% for the summation-at-every-column feature vector and the combination feature vector respectively. The summation-at-every-row feature vector as a supplementary feature improves the classification performance but burdens the computation load of classification.
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on (Volume:1 )
Date of Conference: 13-14 Oct. 2010