Blind source separation method based on Principal Component Analysis and variational Bayesian independent component analysis
Zhi Nong Li · Journal of Nanchang University · 2014
For the deficiencies of the traditional variational Bayesian independent component analysis(VBICA),i.e.the differences resulting from the random initialization in the separation results from different learnings.A blind source separation method based on principal component analysis(PCA)and VBICA was proposed,where PCA was used to initialize the model parameters.The proposed method was compared with the traditional VBICA method.The simulation results verified the effectiveness of this method,which was superior to the traditional VBICA in the separation performance and the stability of the separation results.It also overcame the deficiencies of the traditional VBICA.