A Combined On-Line PCA-ICA Algorithm for Blind Source Separation

In this paper, we introduce and investigate a method combining principle component analysis (PCA) and independent component analysis (ICA) for blind source separation (BSS). A recursive method for the PCA is applied to meet the demands of a real-time application, and likewise a modified on-line version of the information maximization principle is used. The combined PCA-ICA algorithm, first reduces the dimension of the problem and then separates the signals. Evaluation of the proposed algorithm in a real room shows superior noise suppression capabilities compared to the use of PCA or ICA individually. The proposed algorithm achieves an impressive noise suppression/separation of up to 14 dB with only two microphones. Most importantly this is achieved with negligible distortion of the recovered signal.