Blind source separation with variable step-size method based on a reference separation system

Variable step-size methods are effective methods to solve the problem of choosing step size in adaptive blind source separation process. This paper proposes a novel variable step-size method based on a reference separation system for blind source separation. In view of the correlation between the estimated source signals and original source signals increases along with iteration, the method introduces a reference separation system to approximately estimate the correlation which is utilized to update the step-size. The performance in terms of cross-talking error of the proposed algorithm is analyzed. Simulation results show that the proposed method exhibits superior convergence and better steady-state performance compared with the fixed step-size method in the noise free case, and converges faster than classical variable step-size methods in both stationary and non-stationary environments.