Blind Source Separation Algorithm Using Multilayer Networks
Wei Li · 2008
An algorithm for blind source separation based on multilayer networks is proposed.Using a multilayer network density estimation technique,the algorithm may estimate the unknown probability density functions and its derivative of the score functions of the source signals and the algorithm is truly blind to the particular underlying distribution of the mixed signals.The new algorithm not only outperforms other methods,but also the approach has a better convergence property.The method can be applied to all the blind source separation algorithms where the score function is obtained by a nonlinear function.Simulation results show good performances of the proposed algorithm on both demixing and convergence to the desired solutions.