Convexity in source separation: Models, geometry, and algorithms
Date
2014
Authors
McCoy, M. B.
Cevher, V.
Dinh, Q. T.
Asaei, A.
Baldassarre, L.
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
IEEE Signal Processing Magazine
Print ISSN
1053-5888
Electronic ISSN
Publisher
Institute of Electrical and Electronics Engineers Inc.
IEEE
IEEE
Volume
31
Issue
3
Pages
87 - 95
Language
English
Type
Journal Title
Journal ISSN
Volume Title
Series
Abstract
Source separation, or demixing, is the process of extracting multiple components entangled within a signal. Contemporary signal processing presents a host of difficult source separation problems, from interference cancellation to background subtraction, blind deconvolution, and even dictionary learning. Despite the recent progress in each of these applications, advances in high-throughput sensor technology place demixing algorithms under pressure to accommodate extremely high-dimensional signals, separate an ever larger number of sources, and cope with more sophisticated signal and mixing models. These difficulties are exacerbated by the need for real-time action in automated decision-making systems. © 1991-2012 IEEE.