Blind Source Separation Based on Two-Segment Natural Gradient Algorithm

There are two common algorithms based on natural gradient method,which are fix-step-size algorithm and adaptive step-size algorithm,respectively.Fix-step-size algorithm has a very fast convergence rate in the initial stage of Blind Source Separation.As iteration goes on,however,the step size gradually leads to poor robust performance.On the other hand,for adaptive method,the relatively small initial step size inevitably leads to more times of iteration.To further reduce the contradiction between convergence speed and convergence robust,as well as redundancy computation,two-segment method is therefore proposed in this paper.In addition,the adaptive step formula is modified by the related coefficient with high order.Computer simulation result confirms the effectiveness in improving convergence rate and robustness,as well as reduction of computation in BSS problem.