Markov chain Monte Carlo methods with applications to signal processing

Signal Processing

Volumn 81, Issue 1, 2001, Pages 3-18

  Fitzgerald, W J ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; MARKOV PROCESSES; MATHEMATICAL MODELS; MONTE CARLO METHODS; SPURIOUS SIGNAL NOISE;

BAYESIAN METHODS;

SIGNAL PROCESSING;

EID: 0034817516     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1684(00)00187-0     Document Type: Article

References (34)

1. C. Andrieu, P.M. Djuric, A. Doucet, Model selection by MCMC computation, Signal Processing.
2. C. Andrieu, A. Doucet, P. Duvaut, S.J. Godsill, W.J. Fitzgerald, Simulation-based computational methods for Bayesian signal processing, Proceedings of the 1998 IEEE International Conference Acoustics Speech and Signal, Invited Tutorial Paper, 1998.
3. C. Andrieu, A. Doucet, S.J. Godsill, W.J. Fitzgerald, An Introduction to the Theory and Applications for Simulation Based Computational Methods in Bayesian Signal Processing, Cambridge University Engineering Dept CUED/F-INFENG/TR.324, 1998.
4. J.M. Bernardo, A.F.M. Smith, Bayesian Theory, Wiley, New York, 1994.
5. J. Besag, A candidate's formula: a curious result in Bayesian prediction, Biometrika 76 (1) (1989) 183.
6. A. Doucet, C. Andrieu, W.J. Fitzgerald, Interacting Markov chains for sequential Bayesian estimation, Workshop HSSS On-line Monte Carlo Filtering and Prediction, Pavia, Italy, June 1999.
7. S. Duane, A.D. Kennedy, B.J. Pendleton, D. Roweth, Hybrid Monte Carlo, Phys. Lett. B 195 (2) (1987) 216-222.
8. W.J. Fitzgerald, S.J. Godsill, A.C. Kokaram, J.A. Stark, Bayesian methods in signal and image processing, in: J.M. Bernardo, J.O. Berger, A.P. Dawid, A.F.M. Smith (Eds.), Bayesian Statistics, Vol. 6, Oxford University Press, Oxford, 1998, pp. 239-254.
9. A.E. Gelfand, A.F.M. Smith, Sampling based approaches to calculating marginal densities, J. Am. Stat. Assoc. 85 (410) (1990) 398-409.
10. W.R. Gilks, S. Richardson, D.J. Spieglehalter, Markov Chain Monte Carlo in Practice, Chapman & Hall, New York, 1996.
11. S.J. Godsill, P.J.W. Rayner, Digital Audio Restoration, Springer, New York, June 1998.
12. P.J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika 82 (1995) 711-732.
13. W.K. Hastings, Monte Carlo sampling methods using Markov chains and their applications, Biometrika 57 (1970) 97-109.
14. B. Kannan, W.J. Fitzgerald, A numerical Bayesian approach for DOA and frequency estimation of exponential signals in Gaussian and non-Gaussain noise, Proceedings of the Nineth IEEE SP Workshop on Statistical Signal and Array Processing, 1998.
15. A.C. Kokaram, Motion Picture Restoration, Springer, Berlin, 1998.
16. V.B. Manimohan, W.J. Fitzgerald, Blind frequency offset and delay estimation of linearly modulated signals using second order cyclic statistics, ICASSP'98, Vol. 4, Seattle, USA, May 1998, pp. 2337-2340.
17. E. Marinari, G. Parisi, Simulated tempering: a new Monte Carlo scheme, Europhys. Lett. 19 (6) (1992) 451-458.
18. S.P. Meyn, R.L. Tweedie, Markov Chains and Stochastic Stability, Springer, Berlin, 1993.
19. R. Morris, W.J. Fitzgerald, A sampling based approach to line scratch removal from motion picture frames, Proceedings of the IEEE International Conference on Image Processing, Lausanne, Switzerland, September 1996.
20. J. Noga, W.J. Fitzgerald, Modelling correlated Rayleigh distributed clutter using the Gibbs sampler, American Statistical Society, Section on Bayesian Statistics, 1997, pp. 234-239.
21. J. Noga, W.J. Fitzgerald, Modelling sea clutter using conditional heteroscedastic models, EUSIPCO98, Rhodes, Greece.
22. J. Noga, W.J. Fitzgerald, Radar detection in spatially correlated sea clutter using a Kalman filter based CFAR detector, RSSP98, Peebles, Scotland.
23. J.J.K. Ó Ruanaidh, W.J. Fitzgerald, Interpolation of missing samples for audio restoration, Electron. Lett. 30 (8) (1994) 622.
24. J.J.K. O'Ruanaidh, W.J. Fitzgerald, Numerical Bayesian Methods Applied to Signal Processing, Springer, New York, 1996.
25. P.J.W. Rayner, S.J. Godsill, The detection and correction of artefacts in degraded gramophone recordings, Proceedings of the IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics, 1991.
26. C.P. Robert, G. Casella, Monte Carlo Statistical Methods, Springer, Berlin, 1999.
27. J.J. Rooney, W.J. Fitzgerald, Bayesian parameter estimation and model selection in non-Gaussian noise environments, Proceedings of the Third I.M.A. Conference on the Application of Mathematics in Signal Processing, Warwick, December 1992.
28. J.J. Rooney, W.J. Fitzgerald, Bayesian parameter estimation and model selection in impulsive noise environments, Proceedings of the ICASSP 1993, Minneapolis, April 1993.
29. R. Rosales, J.A. Stark, W.J. Fitzgerald, S.B. Hladky, Bayesian estimation of ion channel hidden Markov models, Biophys. J. 74 (1998) A325.
30. J.A. Stark, W.J. Fitzgerald, S.B. Hladky, Idealisation of Patch Clamp records using an any-level modelling scheme, Biophys. J. 74 (1998) A321.
31. L. Tierney, Markov chains for exploring posterior distributions (with discussion), Ann. Stat. 22 (4) (1994) 1701-1762.
32. L. Tierney, A note on Metropolis-Hastings kernels for general state spaces, School of Statistics, University of Minnesota, No. 606, June 1995.
33. S.V. Vaseghi, Algorithms for the restoration of archived gramophone recordings, Ph.D. Thesis, Cambridge University Engineering Department, England, 1988.
34. M.D. Wu, W.J. Fitzgerald, Bayesian multimodal evidence computation by adaptive tempering MCMC, Proceedings of the 1995 Maximum Entropy Conference, Sante Fe, Kluwer, Academic Publishers, Dordrecht.