Single Channel Source Separation Using Non-Gaussian NMF and Modified Hilbert Spectrum

In this paper, a new and powerful method for Blind source separation for single channel mixtures in the noisy environment is presented. This method is based on nonnegative matrix factorization in which modified Hilbert spectrum is employed. In the proposed algorithm, a modified EEMD is offered to transfer the signal to the special intrinsic mode functions (IMF). We used the local spectrums (LoMS) as artificial observations. In order to make estimated spectrum using NMF, the maximization of non-Gaussianity is used. The simulation result indicates that the proposed method improves the quality of reconstruction better than traditional NMF and decreases the time consumption time, compare to more than NMF2D.