A Fixed-point Blind Source Separation Iterative Algorithm Based on ICA

This paper introduces a fixed-point learning algorithm based on ICA(Independent Component Analysis),the model and process of this algorithm and simulation results are presented.Here we adopted kurtosis as the estimation rule of independence.The results of the experiment show that comparing with traditional ICA algorithm based on random grads,this algorithm has many advantages such as fast convergence and needless any dynamic parameter and so on.The algorithm is a highly efficient and reliable method in blind signal separation.