Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm. (2nd June 2014) - Chen, Lei; Zhang, Liyi; Guo, Yanju; Huang, Yong; Liang, Jingyi
Abstract : The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms.