Fourth-order cumulant based sources number estimation from mixtures of unknown number of sources

We consider the source number estimation problem in the presence of unknown spatially nonuniform noise and underdetermined mixtures. We develop a new attractive source number estimator by replacing the covariance with the Fourth-Order (FO) cumulant of the observations. Furthermore, a Modified Minimum Description Length (MMDL) principle is proposed to reduce the divergence of the singular values corresponding to noise thereby improving the performance of the estimator. Simulation experiments validate the superiority of the proposed FO cumulant MMDL method to the conventional Minimum Description Length (MDL) method.