Title :
Approach Based on ICA and SVM to Identify Field Mixed Acoustic Targets
Author :
Huang, Fugui ; Chen, Gong ; Zhang, Xiongwei
Author_Institution :
Dept. of Electron. Inf. Eng., ICE of PLAUST, Nanjing
Abstract :
With ICA to realize the blind separation from mixed acoustic targets, an identification method based on SVM is proposed through extracting LPC feature. SVM is employed to compute the output score and k-means algorithm is used as cluster LPC coefficients. Finally targets are identified by hybrid model. Simulation indicates that this method is effective in mixed acoustic targets identification system
Keywords :
acoustic signal processing; blind source separation; feature extraction; identification; independent component analysis; support vector machines; ICA; SVM; cluster LPC coefficient; independent component analysis; k-means algorithm; mixed acoustic target identification system; support vector machine; Acoustic noise; Acoustic waves; Clustering algorithms; Degradation; Feature extraction; Helicopters; Independent component analysis; Linear predictive coding; Signal analysis; Support vector machines; ICA; LPC; SVM; identification; mixed target;
Conference_Titel :
Radar, 2006. CIE '06. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9582-4
Electronic_ISBN :
0-7803-9583-2
DOI :
10.1109/ICR.2006.343533
