Blind source separation based on improved natural gradient algorithm

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 and reference. The computer simulations have proved the effectiveness of the algorithm.