Blind Source Separation Algorithm Based on Wavelet Smoothing for Super-Gaussian and Sub-Gaussian Signals

In order to separate super-Gaussian and sub-Gaussian signals,this paper uses high-and low-frequency coefficients of wavelet transform as smooth factors,then builds a signal-to-noise ratio objective function,which uses the denominator as prediction error and can be optimized to resolve separable matrix.Simulation shows that this algorithm can separate source signals effectively.