Single Channel Blind Source Separation Based on Dual-Tree Complex Wavelet Transform And Ensemble Empirical Mode Decomposition

Single channel blind source separation (SCBSS) is an important method to separate source signals only from one received signal without any prior information. This paper proposes a SCBSS algorithm based on dual-tree complex wavelet transform (DTCWT) and ensemble empirical mode decomposition (EEMD). First, DTCWT is used to decompose the received signal into several decomposed signals. Then some of them with larger energy are decomposed by EEMD into the intrinsic mode functions, which are selected to constitute virtual signals with the received signal. Finally, the source signals are estimated by Fast-ICA from these virtual multichannel signals. The experimental results show that the performance of the proposed algorithm is significantly improved compared with the SCBSS algorithms based on EEMD and DTCWT respectively.