Sparse Recovery Using Sparse Matrices

In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and make it easy to perform incremental updates to signals. We discuss applications t...

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Bibliographic Details
Published in:Proceedings of the IEEE Vol. 98; no. 6; pp. 937 - 947
Main Authors: Gilbert, Anna, Indyk, Piotr
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Compressive sensing
Computation
Computational complexity
Encoding
expanders
Hardware
Image coding
Mathematical analysis
Mathematics
Matrices
Matrix methods
Recovery
Signal processing
Signal processing algorithms
Sparse matrices
sparse recovery
streaming algorithms
Streams
Testing
Vectors
ISSN:0018-9219, 1558-2256
Online Access:Get full text
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Summary:In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and make it easy to perform incremental updates to signals. We discuss applications to several areas, including compressive sensing, data stream computing, and group testing.
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ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2010.2045092