Abstract:

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.