Sparsity promoted non-negative matrix factorization for source separation and detection

August 11, 2014 in Conference Papers

Abstract:

The effectiveness of non-negative matrix factorization (NMF) depends on a suitable choice of the number of bases, which is often difficult to decide in practice. This paper imposes sparseness on the factorization coefficients in order to determine the number of bases automatically during the decomposition process. The benefit of sparse promotion for NMF is demonstrated through application to sound source separation as well as acoustic-based human fall detection under strong interference.

Links:

IEEE Link PDF

Citation:

Y. Wang, Y. Li, K. C. Ho, A. Zare, and M. Skubic, “Sparsity promoted non-negative matrix factorization for source separation and detection,” in 19th Int. Conf. Digital Signal Proc. (DSP), 2014, pp. 640-645. 
@InProceedings{wang2014sparsity,
Title = {Sparsity promoted non-negative matrix factorization for source separation and detection},
Author = {Wang, Yanlin and Li, Yun and Ho, K. C. and Zare, Alina and Skubic, Marjorie},
Booktitle = {19th Int. Conf. Digital Signal Proc. (DSP)},
Year = {2014},
Month = {Aug.},
Pages = {640-645},
Doi = {10.1109/ICDSP.2014.6900744},
}