Nonlinear Blind Source Separation Based on Compound Kernel Function
Jin Gui-bin · Jisuanji fangzhen · 2010
Kernel Function method has been applied in exploring nonlinear blind source separation for its validity and simplicity.However,single kernel function cannot well solve the absolute nonlinear problem.So a novel separation algorithm based on compound kernel function was proposed.In the algorithm,different kernel function was combined as a whole through variable measure factors,mutual information of separated signal was used as target function to reflect and regulate the measure factors of the compound kernel function,so as to reach an optimum different nonlinear mapping.Simulation results verify the effectiveness of the proposed method;and in solving absolute nonlinear problem,compound kernel function unfolds a better performance than single kernel function.