Blind Extraction Using Fractional Lower-Order Statistics

In traditional method to blindly extract interesting source signals sequentially, the second-order or higher-order statistics of signals are often utilized. However, for impulsive sources, both of the second-order and higher-order statistics may degenerate. Therefore, it is necessary to exploit new method for the blind extraction of impulsive sources. Based on the best compression-reconstruction principle, a novel model is proposed in this work, together with the corresponding algorithm. The proposed method can be used for blind extraction of sources which are distributed from alpha stable process. Simulations are given to illustrate availability and robustness of our algorithm.