关键词: 支持向量机, 概率密度, 激活函数, 定点抽取算法

Abstract: This paper utilizes radial basis function to construct the kernel function and forms a sparse representation of the probability density of the mixed signal based on SVM regression method of Neural network theory，so the expressions of the PDF of the output signals is gotten and a new method of estimating the active function is put forward.A novel BSS algorithm is presented in this paper by combining the PDF estimation with the fixed-point algorithm.The simulations have verified that this algorithm can successfully separate the mixed sub-Gaussian and super-Gaussian source signals.

Key words: support vector machine, probability density function, active function, fixed-point algorithm