Orthogonal AMP for compressed sensing with unitarily-invariant matrices

2016 IEEE Information Theory Workshop, ITW 2016

Volumn , Issue , 2016, Pages 280-284

  Ma, Junjie ^a   Ping, Li ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

approximate message passing (AMP); Compressed sensing; partial orthogonal matrix; replica method; state evolution; unitarily invariant

Indexed keywords

COMPRESSED SENSING; INFORMATION THEORY; ITERATIVE METHODS; MEAN SQUARE ERROR; MESSAGE PASSING; SIGNAL RECONSTRUCTION;

APPROXIMATE MESSAGE PASSING (AMP); ORTHOGONAL MATRIX; REPLICA METHOD; STATE EVOLUTIONS; UNITARILY-INVARIANT;

MATRIX ALGEBRA;

EID: 84999026174     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITW.2016.7606840     Document Type: Conference Paper

References (19)

1. D. L. Donoho, A. Maleki, A. Montanari, "Message-passing al-gorithms for compressed sensing," in Proc. Nat. Acad. Sci., vol. 106, no. 45, Nov. 2009.
2. M. Bayati and A. Montanari, "The dynamics of message passing on dense graphs, with applications to compressed sensing," IEEE Trans. Inf. Theory, vol. 57, no. 2, pp. 764-785, Feb. 2011.
3. D. Donoho, A. Maleki, A. Montanari, "Message passing algorithms for compressed sensing: I. motivation and construction," in Information Theory (ITW 2010, Cairo), 2010 IEEE Information Theory Workshop on, Jan 2010, pp. 1-5.
4. T. Tanaka, "A statistical-mechanics approach to large-system analysis of CDMA multiuser detectors," IEEE Trans. Inf. Theory, vol. 48, no. 11, pp. 2888-2910, Nov. 2002.
5. D. Guo and S. Verdu, "Randomly spread CDMA: asymptotics via statistical physics," IEEE Trans. Inf. Theory, vol. 51, no. 6, pp. 1983-2010, Jun. 2005.
6. S. Rangan, A. Fletcher, V. K. Goyal, "Asymptotic analysis of MAP estimation via the replica method and applications to compressed sensing," IEEE Trans. Inf. Theory, vol. 58, no. 3, pp. 1902-1923, Mar. 2012.
7. J. Vila, P. Schniter, S. Rangan, F. Krzakala, L. Zdeborová, "Adaptive damping and mean removal for the generalized approximate mes-sage passing algorithm," in Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, 2015, pp. 2021-2025.
8. A. Manoel, F. Krzakala, E. W. Tramel, L. Zdeborová, "Sparse estimation with the swept approximated message-passing algorithm," arXiv preprint arXiv:1406.4311, 2014.
9. S. Rangan, A. K. Fletcher, P. Schniter, U. Kamilov, "Inference for generalized linear models via alternating directions and Bethe free energy minimization," arXiv preprint arXiv:1501.01797, 2015.
10. Y. Kabashima and M. Vehkapera, "Signal recovery using expectation consistent approximation for linear observations," in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Jun. 2014, pp. 226-230.
11. B. Cakmak, O. Winther, B. Fleury, "S-AMP: Approximate message passing for general matrix ensembles," in Information Theory Workshop (ITW), 2014 IEEE, Nov. 2014, pp. 192-196.
12. A. Fletcher, M. Sahraee-Ardakan, S. Rangan, P. Schniter, "Ex-pectation consistent approximate inference: Generalizations and conver-gence," arXiv preprint arXiv:1602.07795, 2016.
13. J. Ma and L. Ping, "Orthogonal AMP," arXiv preprint arXiv:1602.06509, 2016.
14. J. Ma, X. Yuan, L. Ping, "Turbo compressed sensing with partial DFT sensing matrix," IEEE Signal Process. Lett., vol. 22, no. 2, pp. 158-161, Feb. 2015.
15. A. M. Tulino and S. Verdú, Random matrix theory and wireless communications. Now Publishers Inc, 2004, vol. 1.
16. S. M. Kay, Fundamentals of statistical signal processing: estimation theory. NJ: Prentice-Hall PTR, 1993.
17. M. Vehkapera, Y. Kabashima, S. Chatterjee, "Analysis of regularized LS reconstruction and random matrix ensembles in compressed sensing," in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Jun. 2014, pp. 3185-3189.
18. A. Tulino, G. Caire, S. Verdu, S. Shamai, "Support recovery with sparsely sampled free random matrices," IEEE Trans. Inf. Theory, vol. 59, no. 7, pp. 4243-4271, Jul. 2013.
19. H. A. Van der Vorst, Iterative Krylov methods for large linear systems. Cambridge University Press, 2003, vol. 13.