NMF Algorithm Based on Extended Kullback-Leibler Divergence

Blind signal separation is the separation of unknown target source signals from observed mixed signals. In this paper, a new non-negative matrix decomposition (NMF) method is proposed for the separation of mixed signals in noise environment without prior conditions. Based on the existing NMF algorithm, the improved optimization model was designed by adding random noise, and the form of kullback-Ieibler dispersion was extended. Theoretical analysis and simulation experiments show that the algorithm proposed in this paper is superior to the existing algorithm in estimating the source signal, especially when the signal is equal to noise energy and the mixed signal is completely immersed in noise, the recovery effect of the source signal is more obvious than the existing algorithm.