Blind source separation based on improved natural gradient algorithm

Abstract

The natural gradient algorithm is the most basic independent component analysis (ICA) algorithm. Because the traditional natural gradient algorithm adopts fixed-step-size, the choice of step size directly affects the convergence speed and steady-state performance. This paper proposes an improved natural gradient algorithm by using the difference between the separation matrixes to control the factor of step size. The algorithm is a good solution to the trade-offs problems of convergence speed and steady-state performance. Meanwhile, the complexity of the algorithm is lower than the algorithm of reference [2] and reference [11]. The computer simulations have proved the effectiveness of the algorithm.