A novel algorithm called double convergence factors FastICA (DCF-FastICA) was proposed to solve the problem that the FastICA algorithm is sensitive to the initial weights.Two FastICA algorithms with different step size factors were combined in this method,and the combination coefficient was adjusted using the gradient algorithm until the optimal separation matrix was obtained.Theoretical analysis and experimental simulation showed that the proposed algorithm can produce better separation result compared with the previous improved algorithms,the problem of initial weights sensitivity could be resolved with almost no loss of separation precision,the average separation speed is improved nearly 70% and the number of iterations reduced nearly 80% compared with the original FastICA algorithm.
