Adaptive algorithms for sparse system identification

Signal Processing

Volumn 91, Issue 8, 2011, Pages 1910-1919

  Kalouptsidis, Nicholas ^a   Mileounis, Gerasimos ^a   Babadi, Behtash ^b   Tarokh, Vahid ^b  

^a UNIVERSITY OF ATHENS   (Greece)

^b HARVARD UNIVERSITY   (United States)

Author keywords

Adaptive estimation; Compressive sensing; Expectation Maximization; Kalman filtering; Volterra series

Indexed keywords

ADAPTIVE ESTIMATION; COMPRESSIVE SENSING; EXPECTATION-MAXIMIZATION; KALMAN FILTERING; VOLTERRA SERIES;

BLIND SOURCE SEPARATION; KALMAN FILTERS; MAXIMUM PRINCIPLE; OPTIMIZATION; POWER AMPLIFIERS; SIGNAL RECONSTRUCTION;

ADAPTIVE ALGORITHMS;

EID: 79955482266     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2011.02.013     Document Type: Article

References (30)

1. A. Bruckstein, D. Donoho, and M. Elad From sparse solutions of systems of equations to sparse modeling of signals and images SIAM Review 51 1 2009 34 81
2. W. Bajwa, J. Haupt, G. Raz, and R. Nowak Compressed channel sensing Proceedings of the IEEE CISS 2008 5 10
3. Y. Chen, Y. Gu, and A. Hero Sparse LMS for system identification Proceedings of the IEEE ICASSP 2009
4. B. Babadi, N. Kalouptsidis, and V. Tarokh Comparison of spaRLS and RLS algorithms for adaptive filtering Proceedings of the IEEE Sarnoff Symposium 2009
5. D. Angelosante, and G. Giannakis RLS-weighted LASSO for adaptive estimation of sparse signals Proceedings of the IEEE ICASSP 2009
6. N. Vaswani Kalman filtered compressed sensing Proceedings of the IEEE ICIP 2008 893 896
7. A. Carmi, P. Gurfil, D. Kanevsky, A simple method for sparse signal recovery from noisy observations using Kalman filtering, IBM Research Report.
8. D. Duttweiler Proportionate normalized least-mean-squares adaptation in echo cancellers IEEE Trans. Speech Audio Process. 8 5 2000 508 518
9. S. Benedetto, and E. Biglieri Principles of Digital Transmission: With Wireless Applications 1999 Springer
10. J. Tropp Just relax: convex programming methods for identifying sparse signals IEEE Trans. Inf. Theory 51 2 2006 1030 1051 (Pubitemid 46444890)
11. S. Chen, D. Donoho, and M. Saunders Atomic decomposition by basis pursuit SIAM J. Sci. Comput. 20 1 1998 33 61 (Pubitemid 128689501)
12. M. Figueiredo, R. Nowak, and S. Wright Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems IEEE J. Sel. Topics Signal Process. 1 4 2007 586 597 (Pubitemid 351276802)
13. A. Beck, and M. Teboulle A fast iterative shrinkage-thresholding algorithm for linear inverse problems SIAM J. Imaging Sci. 2 1 2009 183 202
14. R. Tibshirani Regression shrinkage and selection via the LASSO J. R. Stat. Soc. B 58 1 1996 267 288
15. Z. Ben-Haim, Y. Eldar, M. Elad, Near-oracle performance of basis pursuit under random noise, IEEE Trans. Signal Process., submitted for publication, Arxiv preprint 0903.4579.
16. L. Ljung General structure of adaptive algorithms: adaptation and tracking N. Kalouptsidis, S. Theodoridis, Adaptive System Identification and Signal Processing Algorithms 1993
17. A. Sayed Adaptive Filters 2008 Wiley-IEEE Press
18. A. Dempster, N. Laird, and D. Rubin Maximum likelihood from incomplete data via the EM algorithm J. R. Stat. Soc. B 39 1 1977 1 38
19. M. Feder, Statistical signal processing using a class of iterative estimation algorithms, Ph.D. Thesis, MIT, Cambridge, MA, 1987.
20. M. Figueiredo, and R. Nowak An EM algorithm for wavelet-based image restoration IEEE Trans. Image Process. 12 8 2003 906 916
21. E. Weinstein, A. Oppenheim, M. Feder, and J. Buck Iterative and sequential algorithms for multisensor signal enhancement IEEE Trans. Signal Process. 42 4 1994 846 859
22. A. Jazwinski Adaptive filtering Automatica 5 1969 475 485
23. G. Carayannis, D. Manolakis, and N. Kalouptsidis A fast sequential algorithm for least-squares filtering and prediction IEEE Trans. Acoust. Speech Signal Process. 31 6 1983 1394 1402 (Pubitemid 14552338)
24. D. Slock, and T. Kailath Numerically stable fast transversal filters for recursive least squares adaptive filtering IEEE Trans. Signal Process. 39 1 1991 92 114
25. G.-O. Glentis, P. Koukoulas, and N. Kalouptsidis Efficient algorithms for Volterra system identification IEEE Trans. Signal Process. 47 11 1999 3042 3057 (Pubitemid 32081590)
26. E. Candès, M. Wakin, and S. Boyd Enhancing sparsity by reweighted L1 minimization J. Fourier Anal. Appl. 14 2008 877 905
27. H. Ku, and J. Kenney Behavioral modeling of nonlinear RF power amplifiers considering memory effects IEEE Trans. Microw. Theory Tech. 51 12 2003 2495 2504
28. M. Isaksson, D. Wisell, and D. Ronnow A comparative analysis of behavioral models for RF power amplifiers IEEE Trans. Microw. Theory Tech. 54 1 2006 348 359 (Pubitemid 43119819)
29. A. Bahai, B. Saltzberg, and M. Ergen Multi-Carrier Digital Communications - Theory and Applications of OFDM 2004 Kluwer Academic, Plenum
30. R. Rockafellar Convex Analysis 1970 Princeton University Press