Feature Extraction Technique of Acoustic Target Based on Wavelet Packet Energy and Principal Component Analysis

摘要：

　　A feature extraction method based on wavelet packet energy distribution and correlation coefficient has been put forward to recognize the different acoustic targets in this paper.In view of the characteristics of acoustic target,we employed principal component analysis (PCA) to compress data set of the features extracted based on wavelet packet energy distribution and correlation coefficient.The results have been inputted into the neural network as eigenvectors for pattern recognition.Simulation results indicate that the method suggested in this paper have a recognition rate better than 8% with only wavelet packet energy method,thus verifying its effectiveness.

关键词： Feature extraction Acoustic target Wavelet packet energy Principal component analysis (PCA)

作者: Yonglin Lü Zhenghua Zi

作者单位: Chuxiong Normal University, Chuxiong, 675000, China Kunming Institute of Physics, Kunming, 650223, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 687-691

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）