Browsing by Subject "Decision-making systems"

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    Convexity in source separation: Models, geometry, and algorithms
    (Institute of Electrical and Electronics Engineers Inc., 2014) McCoy, M. B.; Cevher, V.; Dinh, Q. T.; Asaei, A.; Baldassarre, L.
    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.