Bayesian learning for sparse signal reconstruction

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 6, Issue , 2003, Pages 601-604

  Wipf, David P ^a   Rao, Bhaskar D ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; INVERSE PROBLEMS; PROBLEM SOLVING;

BAYESIAN LEARNING;

SIGNAL RECONSTRUCTION;

EID: 0141854016     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. B. D. Rao, "Signal processing with the sparseness constraint," Proc. ICASSP, vol. 3, pp. 1861-1864, May 1998.
2. S.S. Chen, D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM Journal on Scientific Computing, vol. 20, no. 1, pp. 33-61, 1999.
3. Michael E. Tipping, "Sparse bayesian learning and the relevance vector machine," Journal of Machine Learning, vol. 1, pp. 211-244, 2001.
4. Bhaskar D. Rao and Kenneth Kreutz-Delgado, "An affine scaling methodology for best basis selection," IEEE Transactions on Signal Processing, vol. 47, no. 1, pp. 187-200, January 1999.
5. I. F. Gorodnitsky and B. D. Rao, "Sparse signal reconstruction from limited data using focuss: A re-weighted minimum norm algorithm," IEEE Trans. on Signal Processing, vol. 45, no. 3, pp. 600-616, March 1997.
6. David J. C. MacKay, "Bayesian interpolation," Neural Computation, vol. 4, no. 3, pp. 415-447, 1992.
7. R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, 1990.
8. D. G. Luenberger, Linear and Nonlinear Programming, Addison-Wesley, Reading, Mass., 1984.
9. B.D. Rao, et. al., "Subset selection in noise based on diversity measure minimization," To Appear in IEEE Trans. Signal Processing, 2003.