A statistically sparse decomposition principle for underdetermined blind source separation

The underdetermined case in blind source separation, that is, separation of n sources from m (m1 -norm solution. Second, we present a new sparse representation based on second order statistic, which is called statistically sparse decomposition principle (SSDP). Finally, speech signal experiments demonstrate the performance of the approach.