Title :
Bound constrained weighted NMF for industrial source apportionment
Author :
Limem, A. ; Puigt, M. ; Delmaire, G. ; Roussel, G. ; Courcot, D.
Author_Institution :
LISIC, Univ. Lille Nord de France, Calais, France
Abstract :
In our recent work, we introduced a constrained weighted Non-negative Matrix Factorization (NMF) method using a β-divergence cost function. We assumed that some components of the factorization were known and were used to inform our NMF algorithm. In this paper, we are provided some intervals of possible values for some factorization components. We thus introduce an extended version of our previous work combining an improved divergence expression and some matrix normalizationswhile using the known / bounded information. Some experiments on simulated mixtures of particulate matter sources show the relevance of these approaches.
Keywords :
blind source separation; matrix decomposition; β-divergence cost function; bound constrained weighted NMF; factorization components; industrial source apportionment; matrix normalizations; nonnegative matrix factorization; particulate matter sources; Chemicals; Indexes; Linear matrix inequalities; Noise measurement; Signal to noise ratio; Sparse matrices; Vectors; Beta divergence; Blind source separation; Non-negative matrix factorization; Normalization;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2014 IEEE International Workshop on
Conference_Location :
Reims
DOI :
10.1109/MLSP.2014.6958851