Backward-forward combined convolutive blind source separation

Many blind source separation algorithms only try to find the estimation of original signals and the demixing system. However, finding the mixing system is also an important task, which is a representation for the recording environment. Direct inversing the mixing system will introduce many noises. We proposed a correlation based backward-forward combined algorithm to do blind source separation. In the proposed algorithm, an alternative optimization strategy is applied. The estimation of mixing/de-mixing system is used as an initial guess to optimize the demixing/ mixing system iteratively. This alternative optimization algorithm can obtain better estimation for mixing and de-mixing system at the same time. In addition, it can reduce the chance to be tracked into a local minimal. As a result, we can get a better estimation for the sources. Good experimental results were obtained on both simulated and real signals.