A Robust Method for Mixing Matrix Estimationin Blind Source Separation

To solve the problems of traditional methods for mixing matrix estimation in blind source separation such as poor robustness, the defect that separation performance is vulnerable to the initial value and low estimation accuracy, Artificial Bee Colony (ABC) algorithm is applied to blind source separation. Combining with the characteristics of mixing matrix estimation for sparse signals separation, a two-stage bee colony algorithm based on different searching strategy and encoding mode is proposed to estimate mixing matrix, which can accelerate the convergence rate and enhance estimation precision through bees new searching behavior and collaboration between the bee colonies. The simulation results show that the proposed method can perform very well even in the case of large-scale, weak sparse and low SNR. The proposed method not only has the characteristics of strong robustness and high estimation accuracy compared with existing methods, but also need not a large amount of calculation.