Underdetermined Blind Sources Separation Based on Nonnegative Tri-Matrix Factorization

Jing Zhang; Ye Zhang

doi:10.4028/www.scientific.net/AMR.971-973.1843

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 971-973Underdetermined Blind Sources Separation Based on...

Underdetermined Blind Sources Separation Based on Nonnegative Tri-Matrix Factorization

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 971-973)

Pages:

1843-1846

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.971-973.1843

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Online since:

June 2014

Authors:

Jing Zhang, Ye Zhang

Keywords:

Blind Source Separation, NMF, NTMF, Sparse Signals

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