DocumentCode
269831
Title
Static and Dynamic Source Separation Using Nonnegative Factorizations: A unified view
Author
Smaragdis, Paris ; FeÌvotte, CeÌdric ; Mysore, Gautham J. ; Mohammadiha, Nasser ; Hoffman, Matthias
Author_Institution
Comput. Sci. Dept., Univ. of Illinois, Urbana, IL, USA
Volume
31
Issue
3
fYear
2014
fDate
May-14
Firstpage
66
Lastpage
75
Abstract
Source separation models that make use of nonnegativity in their parameters have been gaining increasing popularity in the last few years, spawning a significant number of publications on the topic. Although these techniques are conceptually similar to other matrix decompositions, they are surprisingly more effective in extracting perceptually meaningful sources from complex mixtures. In this article, we will examine the various methodologies and extensions that make up this family of approaches and present them under a unified framework. We will begin with a short description of the basic concepts and in the subsequent sections we will delve in more details and explore some of the latest extensions.
Keywords
matrix decomposition; source separation; complex mixtures; dynamic source separation model; matrix decompositions; nonnegative factorizations; static source separation model; Data mining; Data models; Matrix decomposition; Probabilistic logic; Signal processing algorithms; Source separation; Time-frequency analysis;
fLanguage
English
Journal_Title
Signal Processing Magazine, IEEE
Publisher
ieee
ISSN
1053-5888
Type
jour
DOI
10.1109/MSP.2013.2297715
Filename
6784107
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