Quadratic Independent Component Analysis Based on Sparse Component

Abstract

In this paper, a novel signal blind separation using adaptive multi-resolution independent component analysis based on sparse component is presented. This method separates mixed signal based on quadratic function and sparse representation. The quadratic function can be interpreted as the time-frequency function or time-scale function, or other. The sparse expression is the original signal through the dictionary to get their coefficients. Most of the coefficients is very small, close to zero, can greatly save separate computing time. At the same time this method can filter out the noise. The argorithm extends the separate technology from time-frequency domain to sparse mutil-resolution domain. The experimental result showed the method can be effective separation of mixed signals. And it shows that the method is feasible.