Algorithm Research On Blind Separation Of Acoustic Mixtures

During the past decade, Blind Source Separation-BSS has been a focus in the research area of signal processing. Ranging from wireless communication to medical signals processing, to image enhancement and to audio mixtures separation, BSS is a powerful tool to tackle those problems because it can reconstruct the original signals from the observed signals without any prior knowledge of the mixing system and source signals.BSS for audio mixtures is original intention of BSS technique, and also is a challenging problem in signal processing realm. The fundamental theories of BSS and main methods for audio separation are introduced and investigated in this thesis. Research works of this thesis are as follows:1. The relation of FFT size and the length of reverberation in BSS implementation in frequency domain and its influence on the performance of separation are investigated.2. A new fixed-point ICA algorithm is introduced into BSS for audio mixtures, and an algorithm of BSS based on FIR matrix algebra with block implementation is given. The experiments demonstrate the efficiency of the new algorithm.3. A new algorithm based on Immunity Algorithm with good global convergence, which can overcome the defect of the existing algorithms for separation of audio mixtures in reverberant environment is proposed.