PCA与ICA相结合的语音信号盲分离OACSCDCSTPCD
Blind separation for speech signal based on PCA and ICA
针对ICA用于语音信号盲分离时,由于数据量过大、迭代次数过多引起的收敛速度慢的问题,采用一种PCA和ICA相结合的盲分离算法PCA-ICA.通过PCA对混合语音信号进行白化处理,消除了原始各道数据间的二阶相关性.在仿真实验中,采用相似系数矩阵作为评价混合语音信号分离效果的标准,结果表明PCA-ICA算法与ICA算法相比,在达到几乎相同的相似系数矩阵的情况下,迭代次数减少了90％,从而分离速度提高了3倍,有效地解决了ICA分离算法收敛速度慢的问题.
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 …查看全部>>
王玉静;于凤芹
江南大学物联网工程学院,江苏无锡214122江南大学物联网工程学院,江苏无锡214122
信息技术与安全科学
盲源分离独立分量分析主成分分析
blind source separation independent component analysis principle component analysis
《计算机工程与应用》 2012 (10)
汉语语音信号的时频感知新特征提取的研究
124-127,4
国家自然科学基金(No.61075008).
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