[1] M. Fallon and S.J. Godsill. Multi target acoustic source tracking using track before detect. In Proc. IEEE WASPAA, October 2007.
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[2] N. Whiteley, S. Singh, and S. J. Godsill. Auxiliary particle implementation of the Probability Hypothesis Density filter. In Proc. of 5th International Symposium on Image and Signal Processing and Analysis. IEEE, September 2007.
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[3] S.J. Godsill, J. Vermaak, K-F. Ng, and J-F. Li. Models and algorithms for tracking of manoeuvring objects using variable rate particle filters. Proc. IEEE, 95(5), May 2007.
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[4] O. Cappé, S.J. Godsill, and E.Moulines. An overview of existing methods and recent advances in sequential monte carlo. Proc. IEEE, 95(5), May 2007.
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[6] N. Whiteley, A. T. Cemgil, and S. J. Godsill. Sequential Inference of Rhythmic Structure in Musical Audio. In Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 07), pages 1321-1324. IEEE, April 2007.
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[6] N. Whiteley, A. T. Cemgil, and S. J. Godsill. Sequential Inference of Rhythmic Structure in Musical Audio. In Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 07), pages 1321-1324. IEEE, April 2007.
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[7] P. H. Peeling, C. Li, and S. J. Godsill. Poisson point process modeling for polyphonic music transcription. Journal of the Acoustical Society of America Express Letters, 121(4):EL168-EL175, April 2007. Reused with permission from Paul Peeling, The Journal of the Acoustical Society of America, 121, EL168 (2007). Copyright 2007, Acoustical Society of America.
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[8] S.J. Godsill. Particle filters for continuous-time jump models in tracking applications. In ESAIM: PROCEEDINGS of Oxford Workshop on Particle Filtering, 2007. (To Appear).
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[9] S.J. Godsill, A.T. Cemgil, C. Fevotte, and P.J. Wolfe. Bayesian computational methods for sparse audio and music processing. In 15th European Signal Processing Conference. EURASIP, 2007.
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[10] S.K. Pang, J-F. Li, and S.J. Godsill. Models and algorithms for detection and tracking of coordinated groups. In Proc. of 5th International Symposium on Image and Signal Processing and Analysis. IEEE, Sep 2007.
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[11] P. H. Peeling, A. T. Cemgil, and S. J. Godsill. A probabilistic framework for matching music representations. In Proc. ISMIR, 2007.
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[12] A. T. Cemgil, P. H. Peeling, O. Dikmen, and S. J. Godsill. Prior structures for time-frequency energy distributions. In Proc. IEEE WASPAA, 2007.
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[13] N. Whiteley, A.M. Johanssen, and S.J. Godsill. Efficient monte carlo filtering for discretely observed jumping processes. In Proc. IEEE SSP, 2007.
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[14] G. Yang and S.J. Godsill. Bayesian inference for continuous-time ARMA models driven by jump diffusions. In Proc. IEEE SSP, 2007.
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[15] A. T. Cemgil, S. J. Godsill, and C. Fevotte. Variational and Stochastic Inference for Bayesian Source Separation. Digital Signal Processing, 17, 2007.
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[16] K-F. Ng, J-F. Li, S.J. Godsill, and S.K. Pang. Multitarget initiation, tracking and termination using bayesian monte carlo methods. The Computer Journal, 2007. (To appear).
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[17] G. Ridgway and S.J. Godsill. Bayesian image modelling of cdna microarray spots. Signal Processing Letters, 2007. toappear.
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[18] C. Févotte, B. Torrésani, L. Daudet, and S. J. Godsill. Sparse linear regression with structured priors and application to denoising of musical audio. IEEE Trans. Audio, Speech and Language Processing, 2007. to appear.
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[19] M. Fallon, S. Godsill, and A. Blake. Joint acoustic source location and orientation estimation using sequential monte carlo. In Proc. of the 9th Int. Conference on Digital Audio Effects (DAFx'06), Montreal, Canada, September 2006.
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[20] H. Lin and S. Godsill. Real-time bayesian gsm buzz removal. In Proc. of the 9th Int. Conference on Digital Audio Effects (DAFx'06), Montreal, Canada, September 2006.
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[21] J.W. Yoon and S.J. Godsill. Bayesian inference for multidimensional nmr image reconstruction. September 2006.
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[22] C. Févotte and S. Godsill. Sparse linear regression in unions of bases via Bayesian variable selection. IEEE Signal Processing Letters, 13(7):441-444, July 2006.
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[23] C. Févotte, L. Daudet, S. J. Godsill, and B. Torrésani. Sparse regression with structured priors: Application to audio denoising. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, May 2006.
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[24] S.J. Godsill and L. Yang. Bayesian inference for continuous-time AR models driven by non-Gaussian lÉvy processes. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, May 2006.
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[25] M. Davy, S.J. Godsill, and J. Idier. Bayesian analysis of polyphonic western tonal music. Journal of the Acoustical Society of America, 119(4), April 2006.
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[26] Ji Won Yoon, Simon Godsill, Eriks Kupce, and Ray Freeman. Deterministic and statistical methods for reconstructing multidimensional nmr spectra. Magnetic Resonance in Chemistry, March 2006.
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[27] W. Ng, S.K. Pang, J.F. Li, and S.J. Godsill. Efficient variable rate particle filters for tracking of manoeuvring targets using an MRF-based motion model. In EUSIPCO, 2006.
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[31] C. Févotte and S. J. Godsill. Blind separation of sparse sources using Jeffrey's inverse prior and the EM algorithm. In Proc. 6th International Conference on Independent Component Analysis and Blind Source Separation (ICA'06), Charleston, SC, USA, Mar. 2006.
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[29] C. Févotte and S. J. Godsill. Blind separation of sparse sources using Jeffrey's inverse prior and the EM algorithm. In Proc. 6th International Conference on Independent Component Analysis and Blind Source Separation (ICA'06), Charleston, SC, USA, Mar. 2006.
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[30] N. Whiteley, A. T. Cemgil, and S. J. Godsill. Bayesian modelling of temporal structure in musical audio. In Proceedings of International Conference on Music Information Retrieval, Victoria, Canada, 2006.
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[31] C. Févotte and S. J. Godsill. Blind separation of sparse sources using Jeffrey's inverse prior and the EM algorithm. In Proc. 6th International Conference on Independent Component Analysis and Blind Source Separation (ICA'06), Charleston, SC, USA, Mar. 2006.
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[32] M. Lombardi and S.J. Godsill. On-line Bayesian estimation of AR signals in symmetric alpha-stable noise. IEEE Trans. on Signal Processing, 2006.
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[33] C. Févotte and S.J. Godsill. A Bayesian approach for blind separation of sparse sources. IEEE Trans. on Speech and Audio Processing, 14(6), 2006.
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[38] C. Févotte and S. J. Godsill. A Bayesian approach to time-frequency based blind source separation. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, October 2005.
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[35] A. T. Cemgil and S. J. Godsill. Efficient variational inference for the dynamic harmonic model. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, October 2005.
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[36] H. Lin and S.J. Godsill. The multi-channel AR model for real-time audio restoration. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, October 2005.
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[37] S.J. Godsill and M. Davy. Bayesian computational models for inharmonicity in musical instruments. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, October 2005.
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[38] C. Févotte and S. J. Godsill. A Bayesian approach to time-frequency based blind source separation. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, October 2005.
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[39] A. T. Cemgil and S. J. Godsill. Efficient Variational Inference for the Dynamic Harmonic Model. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, October 2005.
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[40] J. Vermaak, N. Ikoma, and S.J. Godsill. Sequential Monte Carlo framework for extended object tracking. IEE Proc.-Radar Sonar Navig., 152(5):353-363, October 2005.
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[41] S. J. Godsill and J. Vermaak. Variable rate particle filters for tracking applications. In Proc. IEEE Stat. Sig. Proc., Bordeaux, July 2005.
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[42] P.J. Wolfe and S. J. Godsill. Interpolation of missing data values for audio signal restoration using a Gabor regression model. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, March 2005.
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[43] K. Gilholm, S.J. Godsill, S. Maskell, and D. Salmond. Poisson models for extended target and group tracking. In Proc. SPIE: Signal and Data Processing of Small Targets, 2005.
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[44] W. Ng, J.F. Li, S.J. Godsill, and J. Vermaak. Tracking variable number of targets using sequential Monte Carlo methods. In Proc. IEEE Stat. Sig. Proc., 2005.
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[45] W. Ng, J.F. Li, S.J. Godsill, and J. Vermaak. A review of recent results in multiple target tracking. In International Symposium on Image and Signal Processing and Analysis, 2005.
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[46] J.F. Li, W. Ng, S.J. Godsill, and J. Vermaak. Online multitarget detection and tracking using sequential Monte Carlo methods. In Eighth International Conference on Information Fusion, 2005.
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[47] W. Ng, J.F. Li, S.J. Godsill, and J. Vermaak. Tracking variable number of targets using sequential Monte Carlo method. In 13th European Signal Processing Conference, 2005.
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[48] W. Ng, J.F. Li, S.J. Godsill, and J. Vermaak. A hybrid approach for online joint detection and tracking for multiple targets. In IEEE Aerospace Conference, 2005.
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[49] W. Ng, J.F. Li, S.J. Godsill, and J. Vermaak. Multiple target tracking using a new soft-gating approach and sequential Monte Carlo methods. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2005.
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[50] S.J. Godsill, J.F. Li, and W. Ng. Multiple and extended object tracking with Poisson spatial processes and variable rate filters. In IEEE CAMSAP, 2005.
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[51] A. T. Cemgil and S. J. Godsill. Probabilistic Phase Vocoder and its application to Interpolation of Missing Values in Audio Signals. In 13th European Signal Processing Conference, Antalya/Turkey, 2005. EURASIP.
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[52] A. T. Cemgil, C. Fevotte, and S. J. Godsill. Blind Separation of Sparse Sources using Variational EM. In 13th European Signal Processing Conference, Antalya/Turkey, 2005. EURASIP.
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[53] J. Vermaak, S. Godsill, and P. Perez. Monte Carlo filtering for multi-target tracking and data association. IEEE Tr. Aerospace and Electronic Systems, 41(1):309-332, January 2005.
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[54] J. Vermaak, C. Andrieu, A. Doucet, and S. J. Godsill. Reversible jump Markov chain Monte Carlo strategies for Bayesian model selection in autoregressive processes. J. Time Series Anal., 25(6):785-945, November 2004.
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[55] C. Févotte, S. J. Godsill, and P. J. Wolfe. Bayesian approach for blind separation of underdetermined mixtures of sparse sources. In Proc. 5th International Conference on Independent Component Analysis and Blind Source Separation (ICA'04), Granada, Spain, September 2004.
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[56] S. J. Godsill and J. Vermaak. Models and algorithms for tracking using trans-dimensional sequential Monte Carlo. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2004.
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[57] K. Kashino and S. Godsill. Bayesian estimation of simultaneous musical notes based on frequency domain modelling. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2004.
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[58] N. Ikoma J. Vermaak and S. J. Godsill. Extended object tracking using particle techniques. In Proc. IEEE Aerospace, 2004.
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[59] Cédric Févotte, Simon J. Godsill, and Patrick J. Wolfe. Bayesian approach for blind separation of underdetermined mixtures of sparse sources. In Proc. Internl. Workshop on ICA, 2004.
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[60] S. J. Godsill, A. Doucet, and M. West. Monte Carlo smoothing for non-linear time series. J. Am. Statist. Assoc., 99(465):156-168, 2004.
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[61] P. J. Wolfe, S. J. Godsill, and W.J. Ng. Bayesian variable selection and regularisation for time-frequency surface estimation. Journal of the Royal Statistical Society, Series B, 66(3):575-589, 2004. Read paper (with discussion).
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[62] P.J. Wolfe and S. J. Godsill. A Gabor regression scheme for audio signal analysis. In Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, October 2003.
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[63] J. Vermaak, S. J. Godsill, and A. Doucet. Radial basis function regression using trans-dimensional sequential Monte Carlo. In Proc. IEEE Workshop on Statistical Signal Processing, 2003.
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[64] J. Vermaak, S. J. Godsill, and A. Doucet. Sequential Bayesian kernel regression. In Advances in Neural Information Processing Systems 16, Cambridge, MA. MIT Press, 2003.
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[65] N. Ikoma and S. J. Godsill. Extended object tracking with unknown association, missing observations and clutter using particle filters. In Proc. IEEE Workshop on Statistical Signal Processing, 2003.
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[66] P. J. Wolfe and S. J. Godsill. Efficient alternatives to the Ephraim and Malah suppression rule for audio signal enhancement. EURASIP Journal on Appl. Sig. Processing, 10(1):1043-1051, 2003.
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[67] S. J. Godsill. Discussion of `trans-dimensional Markov chain Monte Carlo' by Peter J. Green (in press). In Highly Structured Stochastic Systems. OUP, 2003.
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[68] M.Davy and S. J. Godsill. Bayesian harmonic models for musical signal analysis (with discussion). In J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith, editors, Bayesian Statistics VII. Oxford University Press, 2003.
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[69] W. Fong, S. J. Godsill, A. Doucet, and M. West. Monte Carlo smoothing with application to speech enhancement. IEEE Trans. on Signal Processing, 50(2):438-449, February 2002. Special issue on Monte Carlo Methods.
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[70] A.C. Kokaram and S.J. Godsill. MCMC for joint noise reduction and missing data treatment in degraded video. IEEE Trans. on Signal Processing, 50(2):189-205, February 2002. Special issue on Monte Carlo Methods.
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[71] M. Davy and S. J. Godsill. Detection of abrupt spectral changes using support vector machines. an application to audio signal segmentation. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002.
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[72] W. Fong and S. J. Godsill. Sequential Monte Carlo simulation of dynamical models with slowly varying parameters: application to audio. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002.
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[73] S. J. Godsill and M. Davy. Bayesian harmonic models for musical pitch estimation and analysis. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002.
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[74] N. M. Haan and S. J. Godsill. Bayesian models for DNA sequencing. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002.
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[75] W. Fong and S. J. Godsill. Sequential Monte Carlo simulation of dynamical models with slowly varying parameters: An extension. In XI European Signal Processing Conference (EUSIPCO), 2002.
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[76] P. J. Wolfe and S. J. Godsill. Bayesian modelling of time-frequency coefficients for audio signal enhancement. In S. Becker, S. Thrun, and K. Obermayer, editors, Advances in Neural Information Processing Systems 15, Cambridge, MA. MIT Press, 2002.
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[77] A. Doucet, S. J. Godsill, and C. P. Robert. Marginal maximum a posteriori estimation using MCMC. Statistics and Computing, 12:77-84, 2002.
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[78] J. Vermaak, C. Andrieu, A. Doucet, and S. J. Godsill. Particle methods for Bayesian modelling and enhancement of speech signals. IEEE Trans. on Speech and Audio Processing, 10(3):173-185, 2002.
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[79] P. J. Wolfe, M. Dörfler, and S. J. Godsill. Multi-Gabor dictionaries for audio time-frequency analysis. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, pages 43-46, October 2001.
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[80] P.J. Wolfe and S. J. Godsill. Simple alternatives to the Ephraim and Malah suppression rule for speech enhancement. In Proc. IEEE Workshop on Statistical Signal Processing, pages 496-499, August 2001.
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[81] N. M. Haan and S. J. Godsill. A time-varying model for DNA sequencing data submerged in correlated noise. In Proc. IEEE Workshop on Statistical Signal Processing, August 2001.
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[82] S. J. Godsill, A Doucet, and M West. Maximum a posteriori sequence estimation using Monte Carlo particle filters. Ann. Inst. Stat. Math., 53(1):82-96, March 2001.
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[83] W. N. W. Fong and S. J. Godsill. Monte carlo smoothing for non-linearly distorted signals. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 6, pages 3997-4000, 2001.
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[84] N.M. Haan and S.J. Godsill. Sequential methods for DNA sequencing. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2001.
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[85] W. Fong and S. J. Godsill. Monte carlo smoothing with application to audio signal enhancement. In Proc. IEEE Workshop on Statistical Signal Processing, pages 18-21, 2001.
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[86] P. Giannopoulos and S. J. Godsill. Estimation of CAR processes observed in noise using Bayesian inference. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2001.
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[87] P.T. Troughton and S.J. Godsill. MCMC methods for restoration of nonlinearly distorted autoregressive signals. Signal Processing, 81(1):83-97, 2001.
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[88] S. J. Godsill. On the relationship between Markov chain Monte Carlo methods for model uncertainty. J. Comp. Graph. Stats., 10(2):230-248, 2001.
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[89] P. J. Wolfe and S. J. Godsill. Perceptually motivated approaches to music restoration. Journal of New Music Research, 30(1):83-92, 2001. Special issue: Music and Mathematics.
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[90] S. J. Godsill, P. J. Wolfe, and W. N. W. Fong. Statistical model-based approaches to audio restoration and analysis. Journal of New Music Research, 30(4):323-338, 2001. Special Issue: Conservation, Restoration and Archiving of Electroacoustic Music.
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[91] S. J. Godsill and T. C. Clapp. Improvement strategies for Monte Carlo particle filters. In A Doucet, J. F. G. De Freitas, and N. J. Gordon, editors, Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.
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[92] S J Godsill, A Doucet, and M West. Methodology for Monte Carlo smoothing with application to time-varying autoregressions. In Proc. International Symposium on Frontiers of Time Series Modelling, February 2000. Institute of Statistical Mathematics, Tokyo.
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[93] A. Doucet, S. J. Godsill, and M. West. Monte Carlo filtering and smoothing with application to time-varying spectral estimation. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume II, pages 701-704, 2000. ISBN 0-7803-6296-9.
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[94] P. J. Wolfe and S. J. Godsill. Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume II, pages 821-824, Istanbul, Turkey, 2000. ISBN 0-7803-6296-9.
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[95] N. M. Haan and S. J. Godsill. Modelling electropherogram data for DNA sequencing using variable dimension MCMC. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume VI, pages 3542-3545, 2000. ISBN 0-7803-6296-9.
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[96] S. J. Godsill. Inference in symmetric alpha-stable noise using MCMC and the slice sampler. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume VI, pages 3806-3809, 2000. ISBN 0-7803-6296-9.
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[97] A. Doucet, S. J. Godsill, and C. Andrieu. On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing, 10:197-208, 2000.
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[98] A Ahmed, P. J.W. Rayner, and S. J. Godsill. Considering non-stationarity for blind signal separation. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1999.
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[99] P. J. Walmsley, S. J. Godsill, and P. J. W. Rayner. Polyphonic pitch tracking using joint Bayesian estimation of multiple frame parameters. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1999.
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[100] S. J. Godsill. MCMC and EM-based methods for inference in heavy-tailed processes with alpha-stable innovations. In Proc. IEEE Signal processing workshop on higher-order statistics, June 1999. Caesarea, Israel.
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[101] S. J. Godsill and E. E. Kuruoglu. Bayesian inference for time series with heavy-tailed symmetric α-stable noise processes. In Proc. Applications of heavy tailed distributions in economics, engineering and statistics, June 1999. Washington DC, USA.
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[102] T. C. Clapp and S. J. Godsill. Fixed-lag blind equalization and sequence estimation in digital communications systems using sequential importance sampling. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 5, pages 2495-2498, March 1999. Arizona.
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[103] C. P. Robert, A. Doucet, and S. J. Godsill. Maximization of marginal posterior distributions using Markov chain Monte Carlo methods. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 3, pages 1753-1756, March 1999. Arizona.
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[104] C. Andrieu and S. J. Godsill. Bayesian separation and recovery of convolutively mixed autoregressive sources. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 3, pages 1733-1736, March 1999. Arizona.
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[105] Paul T. Troughton and Simon J. Godsill. MCMC methods for restoration of quantised time series. Proceedings of the IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, 2:447-451, 1999.
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[106] A Ahmed, P. J.W. Rayner, and S. J. Godsill. Recursive decorrelation for blind convolutive signal separation. In Proc. Independent component analysis and blind signal separation, Aussois, France, January 1999.
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[107] W.J. Fitzgerald, S. J. Godsill, A.C. Kokaram, and A.J. Stark. Bayesian methods in signal and image processing (with discussion). In J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith, editors, Bayesian Statistics VI. Oxford University Press, 1999.
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[108] T. C. Clapp and S. J. Godsill. Fixed-lag smoothing using sequential importance sampling. In J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith, editors, Bayesian Statistics VI, pages 743-752. Oxford University Press, 1999.
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[109] C. Campbell and S. J. Godsill. On a new stochastic version of the EM algorithm. In Proc. European Conference on Signal Processing, September 1998.
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[110] P.T. Troughton and S. J. Godsill. MCMC methods for restoration of nonlinearly distorted autoregressive signals. In Proc. European Conference on Signal Processing, September 1998.
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[111] P.J. Walmsley, S. J. Godsill, and P. J. W. Rayner. Multidimensional optimisation of harmonic signals. In Proc. European Conference on Signal Processing, September 1998.
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[112] S. J. Godsill and P. J. W. Rayner. Digital Audio Restoration: A Statistical Model-Based Approach. Berlin: Springer, ISBN 3 540 76222 1, September 1998.
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[113] C. Andrieu, A. Doucet, and S. J. Godsill. Bayesian blind marginal separation of convolutively mixed discrete sources. In Proc. IEEE Workshop - Neural networks for signal processing, Cambridge, August 1998.
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[114] A.C. Kokaram and S. J. Godsill. Joint noise reduction, motion estimation, missing data reconstruction, and model parameter estimation for degraded motion pictures. In Proc. SPIE, San Diego, July 1998.
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[115] S. J. Godsill and P. J. W. Rayner. Robust reconstruction and analysis of autoregressive signals in impulsive noise using the Gibbs sampler. IEEE Trans. on Speech and Audio Processing, 6(4):352-372, July 1998.
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[116] P.T. Troughton and S. J. Godsill. A reversible jump sampler for autoregressive time series. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume IV, pages 2257-2260, April 1998.
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[117] P.M. Djuric, S. J. Godsill, W. J. Fitzgerald, and P. J. W. Rayner. Detection and estimation of signals by reversible jump Markov chain Monte Carlo computations. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 4, pages 2269-2272, 1998. Seattle.
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[118] P.M. Djuric and S.J. Godsill. Parametric modeling and estimation of time varying spectra. In Proc. Asilomar Conference on Signals and Systems, 1998.
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[119] S. J. Godsill, P. J. W. Rayner, and O. Cappé. Digital audio restoration. In M. Kahrs and K. Brandenburg, editors, Applications of Digital Signal Processing to Audio and Acoustics, pages 133-193. Kluwer Academic Publishers, ISBN 0-7923-8130-0, 1998.
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[120] P. T. Troughton and S. J. Godsill. Bayesian model selection for linear and non-linear time series using the Gibbs sampler. In Mathematics in Signal Processing IV. Oxford University Press, 1998.
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[121] S. J. Godsill and C. H. Tan. Removal of low frequency transient noise from old recordings using model-based signal separation techniques. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1997.
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[122] J. J. Rajan, P. J. W. Rayner, and S. J. Godsill. A Bayesian approach to parameter estimation and interpolation of time-varying autoregressive processes using the Gibbs sampler. IEE Proc. Vision, Image and Signal Processing, 144(4), August 1997.
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[123] P. T. Troughton and S. J. Godsill. Bayesian model selection for time series using Markov chain Monte Carlo. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, April 1997.
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[124] S. J. Godsill. Robust modelling of noisy ARMA signals. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, April 1997.
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[125] S. J. Godsill. Bayesian enhancement of speech and audio signals which can be modelled as ARMA processes. International Statistical Review, 65(1):1-21, 1997.
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[126] S. J. Godsill and A. C. Kokaram. Joint interpolation, motion and parameter estimation for image sequences with missing data. In Proc. EUSIPCO, September 1996.
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[127] S. J. Godsill and P. J. W. Rayner. Robust noise reduction for speech and audio signals. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, May 1996.
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[128] D. C. B. Chan, P. J. W. Rayner, and S. J. Godsill. Multi-channel blind signal separation. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, May 1996.
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[129] A. C. Kokaram and S. J. Godsill. A system for reconstruction of missing data in image sequences using sampled 3D AR models and MRF motion priors. In Computer Vision - ECCV '96, volume II, pages 613-624. Springer Lecture Notes in Computer Science, April 1996.
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[130] S. J. Godsill and P. J. W. Rayner. Robust treatment of impulsive noise in speech and audio signals. In J.O. Berger, B. Betro, E. Moreno, L.R. Pericchi, F. Ruggeri, G. Salinetti, and L. Wasserman, editors, Bayesian Robustness - proceedings of the workshop on Bayesian robustness, May 22-25, 1995, Rimini, Italy, volume 29, pages 331-342. IMS Lecture Notes - Monograph Series, 1996.
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[131] S. J. Godsill and P. J. W. Rayner. Robust noise modelling with application to audio restoration. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1995.
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[132] D. C. B. Chan, P. J. W. Rayner, and S. J. Godsill. Multi-channel blind signal separation by decorrelation. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1995.
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[133] S. J. Godsill and P. J. W. Rayner. A Bayesian approach to the restoration of degraded audio signals. IEEE Trans. on Speech and Audio Processing, 3(4):267-278, July 1995.
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[134] S. J. Godsill. Recursive restoration of pitch variation defects in musical recordings. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 2, pages 233-236, Adelaide, April 1994.
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Keywords: wow, flutter, smoothness, Bayesian regularization
[135] C. M. Hicks and S. J. Godsill. A 2-channel approach to the removal of impulsive noise from archived recordings. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 2, pages 213-216, Adelaide, April 1994.
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[136] S. J. Godsill and P. J. W. Rayner. The restoration of pitch variation defects in gramophone recordings. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1993.
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[137] S. J. Godsill and P. J. W. Rayner. Frequency-domain interpolation of sampled signals. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume I, pages 209-212, Mineapolis, April 1993.
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[138] S. J. Godsill and P. J. W. Rayner. A Bayesian approach to the detection and correction of bursts of errors in audio signals. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, volume 2, pages 261-264, San Francisco, March 1992.
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[139] P. J. W. Rayner and S. J. Godsill. The detection and correction of artefacts in archived gramophone recordings. In Proc. IEEE Workshop on Audio and Acoustics, Mohonk, NY State, Mohonk, NY State, October 1991.
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