Abstract
Most of existing blind source separation (BSS) algorithms are developed by assuming that the mixing matrix is fixed. However, the mixing matrix is commonly time-varying in practical communication system. In this paper, aiming at the problem of non-stationary blind source separation, a fast blind source separation algorithm is proposed by using the exponentially weighted sum of error squares as the cost function and adding the adaptive momentum term to the learning rule. Simulation results show that the proposed algorithm converges quickly and trace time-varying system effectively.
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