Adaptive blind source separation algorithm based on vicinal risk minimizing PDF estimation
基于邻域风险最小化概率密度估计的自适应盲分离算法*

The paper studied the vicinal risk minimization based PDF estimation algorithm using support vector machine, and proposed a new construction algorithm for the vicinity function. Combining with natural gradient batch algorithm, put forward a new adaptive blind source separation algorithm. Analyzed the precision of the solution farther using the generalized gauss mo-del. Carried out the several experiments, which proved that the algorithm could separate the mixtures containing signals with different statistical characteristic. Compared with the widely algorithm based on expirical risk minimization methods, the proposed algorithm has better performance both in the convergent speed and the precision.