Dimensionality reduction method based on PCA and KICA
Zhong Qiang-hui · Systems engineering and electronics · 2011
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 PCA-ICA method,the proposed method achieves a proximate effect when dealing with complicated nonlinear multidimensional mixing signals,but can achieve a better result when dealing with linear multidimensional mixing signals.