Expansion Complex Fast-ICA Algorithm Based on Complex Orthogonal Space

Based on independent component analysis (ICA), this paper discusses the complex signal model of blind source separation. With discussions of characteristics of complex-valued signals, paper establishes mixed and separated model of complex-valued signals used to define an orthogonal decomposition of the complex-valued space. Using the relative gradients method, based on 4-th order cumulant, it sets up a successive independent component recovery fixed-point algorithm of blind separation of complex-valued sources. Finally, under the framework of this discussion, it generates randomly several sub-Gaussian and super-Gaussian signals in order to verify the claims of effectiveness and feasibility, using the algorithm to carry out computer simulation experiments, and analyzes the results. The results shows that the method is very effective.