Accession Number : ADA633835
Title : Computational Methods for Sparse Solution of Linear Inverse Problems
Descriptive Note : Technical rept.
Corporate Author : CALIFORNIA INST OF TECH PASADENA
Personal Author(s) : Tropp, Joel A ; Wright, Stephen J
Report Date : Mar 2009
Pagination or Media Count : 11
Abstract : In sparse approximation problems, the goal is to find an approximate representation of a target signal using a linear combination of a few elementary signals drawn from a fixed collection. This paper surveys the major algorithms that are used for solving sparse approximation problems in practice. Specific attention is paid to computational issues, to the circumstances in which individual methods tend to perform well, and to the theoretical guarantees available. Many fundamental questions in electrical engineering, statistics, and applied mathematics can be posed as sparse approximation problems, which makes the algorithms discussed in this paper versatile tools with a wealth of applications.
Descriptors : *APPROXIMATION(MATHEMATICS) , *INVERSE PROBLEMS , *LINEAR SYSTEMS , *MATRICES(MATHEMATICS) , ALGORITHMS , COMPRESSIVE PROPERTIES , CONVEX SETS , LEAST SQUARES METHOD , NUMERICAL METHODS AND PROCEDURES , OPTIMIZATION , ORTHOGONALITY , SIGNAL PROCESSING , TARGET SIGNATURES , VECTOR ANALYSIS
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE