Underdetermined Blind Sources Separation Based on Nonnegative Tri-Matrix Factorization
Jing Zhang, Ye Zhang · Advanced materials research · 2014
In this paper, a nonnegative tri-Matrix factorization (NTMF) algorithm is proposed for underdetermined blind sources separation with the assumption of that the source signals are nonnegative and sparse. By incorporating the regularization and sparse penalty into the cost function, a novel multiplicative update rules is proposed to solve the problem of UBSS based on NTMF. The simulation results are presented to show the validity and competitive performances of the proposed algorithm.