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Optimization Algorithms for Sparse Representations and Applications

Georgiev, P. and Theis, Fabian J. and Cichocki, A. (2006) Optimization Algorithms for Sparse Representations and Applications. In: Hager, William W., (ed.) Multiscale Optimization Methods and Applications. Nonconvex Optimization and Its Applications, 82. Springer, New York, NY, pp. 85-99. ISBN 978-0-387-29550-3 (e-book), 978-0-387-29549-7 (Print).

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We consider the following sparse representation problem, which is called Sparse Component Analysis: identify the matrices S ∈ IRn×N and A ∈ IRm×n (m ≤ n < N) uniquely (up to permutation of scaling), knowing only their multiplication X = AS, under some conditions, expressed either in terms of A and sparsity of S (identifiability conditions), or in terms of X (Sparse Component Analysis conditions). ...


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Item Type:Book Section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
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Keywords:Sparse Component Analysis - Blind Source Separation - underdetermined mixtures
Subjects:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Owner: Gertraud Kellers
Deposited On:15 Oct 2010 09:09
Last Modified:15 Oct 2010 09:09
Item ID:17322
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