基于主成分分析与核独立成分分析的降维方法

基于主成分分析与核独立成分分析的降维方法

梁胜杰;张志华;崔立林;钟强晖

【期刊名称】《系统工程与电子技术》

【年(卷),期】2011(033)009

【摘要】根据主成分分析(principal component analysis,PCA)法的降维去噪技术和核独立成分分析(kernel independent component analysis,KICA)法的盲源分离技术,提出了一种关于两者的融合方法,即PCA-KICA方法.将该方法应用于线性和非线性高维混合信号的降维处理中,以相关系数和Amari误差为标准,同主成分分析与独立成分分析(principal component analysis-independent component analysis,PCA-ICA)融合方法进行比较.仿真结果标明,PCA-KICA 方法与PCA-ICA方法相比,在处理复杂非线性高维混合信号时效果相当,但在处理线性高维混合信号时的效果较好.%According to the dimensionality reduction technology of principal component analysis (PCA) method and the blind source separation technology of kernel independent component analysis (KICA) method, a combined method, the PCA-KICA method, is presented. It is applied to dealing with some linear and nonlinear multidimensional mixing signal processing. Meanwhile, it is compared with the PCA-independent component analysis (PCA-ICA) method by correlation coefficient and Amari error. Simulation results indicate that, compared with the PGA-ICA method, the proposed method achieves a proximate effect when dealing with complicated nonlinear multidimensional mixing signals, but can achieve a better