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Title:Blind Multichannel Image Deconvolution and Optimum Sparse Approximations
Author(s):Harikumar, G.
Doctoral Committee Chair(s):Bresler, Yoram
Department / Program:Electrical Engineering
Discipline:Electrical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Electronics and Electrical
Abstract:The second problem is one of computing maximally sparse elements of a convex, compact set. This problem arises in a wide range of engineering applications, including regularization of ill-posed problems, design of digital filters with few non-zero coefficients and the computation of sparse approximate solutions to inverse problems. Because the problem is N-P complete, there exists a need to develop heuristic techniques that work well for specific problems. Our contribution is the development of a new class of iterative algorithms for identifying sparse elements of the convex and compact set. We show that the algorithm has good convergence properties through a detailed theoretical analysis and demonstrate its performance on some examples.
Issue Date:1997
Description:150 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.
Other Identifier(s):(MiAaPQ)AAI9737127
Date Available in IDEALS:2015-09-25
Date Deposited:1997

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