Abstract: High order FastICA(fast independent component analysis)algorithm has the characteristics of simple form and quick convergence. However， the algorithm is sensitive to its initial value which affects the convergence effect and even results in nonconvergence if it is not chosen appropriately. In order to solve this problem， a relaxation factor is introduced into high order Newton iterative method. Through the appropriate correction， the improved high order FastICA algorithm can be obtained， which can not only guarantee the convergence speed， but also effectively overcome the initial value sensitivity problem. Applying the algorithm to the separation experiment of speech signals， the result shows that the proposed algorithm effectively separates the mixed signal，and reduces the dependence on the initial value.

Key words: independent component analysis(ICA), FastICA, relaxation factor, initial value sensitivity