One-bit compressed sensing with non-Gaussian measurements

Linear Algebra and Its Applications

Volumn 441, Issue , 2014, Pages 222-239

  Ai, Albert ^a   Lapanowski, Alex ^a   Plan, Yaniv ^a   Vershynin, Roman ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Convex programming; One bit compressed sensing; Quantization; Signal reconstruction

Indexed keywords

CONVEX PROGRAMS; GAUSSIAN RANDOM VECTORS; NON-GAUSSIAN; NON-GAUSSIAN DISTRIBUTION; QUANTIZATION; SINGLE-BIT; SPARSE SIGNALS; SUB-GAUSSIANS;

CONVEX PROGRAMMING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC);

SIGNAL RECONSTRUCTION;

EID: 84889881613     PISSN: 00243795     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.laa.2013.04.002     Document Type: Article

References (11)

1. P.T. Boufounos, R.G. Baraniuk, 1-Bit compressive sensing, in: 42nd Annual Conference on Information Sciences and Systems (CISS), 2008.
2. C. Eldar, and G. Kutyniok Compressed Sensing: Theory and Applications 2012 Cambridge University Press
3. A. Gupta, R. Nowak, B. Recht, Sample complexity for 1-bit compressed sensing and sparse classification, In: International Symposium on Information Theory (ISIT), IEEE, 2010.
4. L. Jacques, J.N. Laska, P.T. Boufounos, R.G. Baraniuk, Robust 1-bit compressive sensing via binary stable embeddings of sparse vectors, Preprint available at < http://arxiv.org/abs/1104.3160 >.
5. M. Ledoux The Concentration of Measure Phenomenon 2001 American Mathematical Society Providence
6. M. Ledoux, and M. Talagrand Probability in Banach Spaces: Isoperimetry and Processes 1991 Springer-Verlag Berlin
7. Y. Plan, R. Vershynin, One-bit compressed sensing by linear programming, Preprint available at < http://arxiv.org/abs/1109.4299 >.
8. Y. Plan, R. Vershynin, Robust 1-bit compressed sensing and sparse logistic regression: a convex programming approach, Preprint available at < http://arxiv.org/abs/1202.1212 >.
9. D. Strook Probability Theory: An Analytic View second ed. 1993 Cambridge University Press
10. T. Tao, and V. Vu Random matrices: the distribution of the smallest singular values Geom. Funct. Anal. 20 1 2010 260 297
11. R. Vershynin Introduction to the non-asymptotic analysis of random matrices Y. Eldar, G. Kutyniok, Compressed Sensing: Theory and Applications 2012 Cambridge University Press