Abstract：To overcome some shortcomings of existing algorithms which separate the mixture of super- and sub-gaussian sources, a parameter kurtosis-dependent flexible Blind Source Separation (BBS) algorithm is proposed. A weighed double Gaussian model is proposed to estimate super-Gaussian and sub-Gaussian probability density. In the framework of natural gradient, model parameter is calculated online by kurtosis. Applied to images mixing, experiment shows the proposed algorithm can successfully separate the mixture of super- and sub-gaussian images. Meanwhile experiment also shows that the proposed algorithm has better performance and convergence than existing algorithms.
2006, Vol. 28 
