A Survey On Theory And Application For Blind Source Separation Algorithm

Blind Signal Processing (BSP) is now one of the hottest and emerging areas in signal with solid theoretical foundations and many potential applications. In fact, BSP has become a very important topic of research and development in many areas, especially radar, sonar, remote sensing, communication systems, biomedical engineering, medical imaging, and image processing, etc. As a branch of BSP, Blind source separation, or source signal separation (BSS), has also become a powerful tool in the areas of signal and image processing. The goal of BSS is to recover the original signals form a set of mixed(observed) signals with no or little a priori knowledge about the sources and mixtures. In this work, we firstly review and discuss the various approaches of linear BSS for both the instantaneous mixtures and convolutive mixtures. Simulations and comparison studies of different techniques have been undertaken to illustrate the main theories and methodologies adopted in solving the BSS problem. And then We analyze the characteristic of typical algorithms. The cases of BSS were done by FastICA and JADE, and the results of simulation proved efficiency of algorithms on separation mixed signals. At the same time, the fundamental theories of BSS and main methods for audio separation are introduced and investigated in this paper.Based on have great effect of nonlinearity function and step-size factor on performance of algorithm, such as convergence rate, squared error, and stability of system, Natural Gradient Algorithm was studied and a new varying step-size algorithm (VS-NGA) based on NGA was proposed, which greatly improved convergence rate of system. In order to reduce computation complexity, sign function was applied to EASI algorithm to form a new algorithm, namely S-EASI. And two novel algorithms based on them were achieved. All of four algorithm were proven successful for simplifying computation and improving convergence speed.In documents on BSS, mixture is always assumed as static, but time-varying...