Title
Blind Separation of Frequency Overlapped Sources Based on Constrained Non-Negative Matrix Factorization
Abstract
The separation of unobserved sources from the observed signals is a fundamental signal processing problem. Most of the proposed techniques for solving this problem rely on independence or at least uncorrelation assumption of source signals. However in some complex systems, the vibration sources are always correlative, and this does not satisfy the assumption condition. Here, a new method based on constrained non-negative matrix factorization (CNMF) is introduced for the case that the sources are correlated only through the overlapping frequencies. In contrast with other reported methods, the proposed method separates source signals in frequency domain without a parametric model of their dependent structure, and is mainly based on the good property of non-negative matrix factorization (NMF) that the sources do not need to be statistically independent. Some numerical simulations are provided to illustrate the feasibility and effectiveness of the proposed method.
Year
DOI
Venue
2007
10.1109/ICDSP.2007.4288556
Cardiff
Keywords
DocType
Volume
frequency overlapped sources,number of sources,blind source separation,matrix decomposition,non-negative matrix factorization,constrained non-negative matrix factorization,statistical independence,numerical simulation,mechanical systems,signal processing,parametric statistics,non negative matrix factorization,vectors,satisfiability,vibrations,frequency domain analysis,complex system,parametric model,frequency domain
Conference
null
Issue
ISSN
ISBN
null
null
1-4244-0882-2
Citations 
PageRank 
References 
1
0.39
5
Authors
2
Name
Order
Citations
PageRank
Ning Li1138.47
Tielin Shi29017.20