计算机工程与应用2012，Vol.48Issue(10)：124-127,4.DOI:10.3778/j.issn.1002-8331.2012.10.027
PCA与ICA相结合的语音信号盲分离
Blind separation for speech signal based on PCA and ICA
摘要
Abstract
In order to solve the slow convergence problem of ICAbased algorithm and high computational cost due to excessive amount data, an blind separation algorithm based on PCA-ICA for speech signal is proposed. PCA is used to remove the second-ordfir correlations among different dimensions of feature from original data. Using similarity coefficient matrix as the separation effect standard, the simulation experiment results show that the proposed method can reduce 90% of iterations and is 3 times faster compared with ICA with the same separation accuracy. Thus the ICA-PCA algorithm effectively solves the slow convergence problem of original ICA method.关键词
盲源分离/独立分量分析/主成分分析Key words
blind source separation/ independent component analysis/ principle component analysis分类
信息技术与安全科学引用本文复制引用
王玉静,于凤芹..PCA与ICA相结合的语音信号盲分离[J].计算机工程与应用,2012,48(10):124-127,4.基金项目
国家自然科学基金(No.61075008). （No.61075008）
