Approximation Algorithms for Model-Based Compressive Sensing

Compressive sensing (CS) states that a sparse signal can be recovered from a small number of linear measurements, and that this recovery can be performed efficiently in polynomial time. The framework of model-based CS (model-CS) leverages additional structure in the signal and provides new recovery...

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Bibliographic Details
Published in:	IEEE transactions on information theory Vol. 61; no. 9; pp. 5129 - 5147
Main Authors:	Hegde, Chinmay, Indyk, Piotr, Schmidt, Ludwig
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm design and analysis Algorithms Approximation Approximation algorithms Approximation methods Compressed sensing Computational modeling Mathematical model Mathematical problems Measurement Optimization Polynomials Sparse matrices combinatorial optimization Compressed sensing approximation algorithms
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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