C. Andrieu and A. Doucet, Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC, IEEE Transactions on Signal Processing, vol.47, issue.10, pp.2667-2676, 1999.
DOI : 10.1109/78.790649

P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, issue.4, pp.711-732, 1995.
DOI : 10.1093/biomet/82.4.711

C. Andrieu, N. Freitas, and A. Doucet, Robust Full Bayesian Learning for Radial Basis Networks, Neural Computation, vol.12, issue.261, pp.2359-2407, 2001.
DOI : 10.1162/neco.1997.9.2.461

C. Andrieu, E. Barat, and A. Doucet, Bayesian deconvolution of noisy filtered point processes, IEEE Transactions on Signal Processing, vol.49, issue.1, pp.134-146, 2002.
DOI : 10.1109/78.890355

J. R. Larocque and J. P. Reilly, Reversible jump MCMC for joint detection and estimation of sources in colored noise, IEEE Transactions on Signal Processing, vol.50, issue.2, pp.231-240, 2002.
DOI : 10.1109/78.978379

J. R. Larocque, J. P. Reilly, and W. Ng, Particle filters for tracking an unknown number of sources, IEEE Transactions on Signal Processing, vol.50, issue.12, pp.2926-2937, 2002.
DOI : 10.1109/TSP.2002.805251

W. Ng, J. P. Reilly, T. Kirubarajan, and J. R. Larocque, Wideband array signal processing using MCMC methods, IEEE Transactions on Signal Processing, vol.53, issue.2, pp.411-426, 2005.
DOI : 10.1109/TSP.2004.838934

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.509.3390

M. Davy, S. J. Godsill, and J. Idier, Bayesian analysis of polyphonic western tonal music, The Journal of the Acoustical Society of America, vol.119, issue.4, pp.2498-2517, 2006.
DOI : 10.1121/1.2168548

URL : https://hal.archives-ouvertes.fr/inria-00120240

M. Hong, M. F. Bugallo, and P. M. Djuric, Joint Model Selection and Parameter Estimation by Population Monte Carlo Simulation, IEEE Journal of Selected Topics in Signal Processing, vol.4, issue.3, pp.526-539, 2010.
DOI : 10.1109/JSTSP.2010.2048385

M. N. Schmidt and M. Mørup, Infinite non-negative matrix factorization, Proceedings of the 18th European Signal Processing Conference (EUSIPCO), 2010.

D. V. Rubtsov and J. L. Griffin, Time-domain Bayesian detection and estimation of noisy damped sinusoidal signals applied to NMR spectroscopy, Journal of Magnetic Resonance, vol.188, issue.2, pp.367-379, 2007.
DOI : 10.1016/j.jmr.2007.08.008

A. Roodaki, Signal Decompositions using Trans-dimensional Bayesian Methods, 2012.
URL : https://hal.archives-ouvertes.fr/tel-00765464

A. Roodaki, J. Bect, and G. Fleury, Note on the computation of the Metropolis- Hastings ratio for Birth-or-Death moves in trans-dimensional MCMC algorithms for signal decomposition problems, ), ´ Ecole Supérieure d' ´ Electricité (Supélec), 2012.

J. L. Jannink and R. L. Fernando, On the Metropolis-Hastings Acceptance Probability to Add or Drop a Quantitative Trait Locus in Markov Chain Monte Carlo-Based Bayesian Analyses, Genetics, vol.166, issue.1, pp.641-643, 2004.
DOI : 10.1534/genetics.166.1.641

M. J. Sillanpaa, D. Gasbarra, and E. Arjas, Comment on "On the Metropolis-Hastings Acceptance Probability to Add or Drop a Quantitative Trait Locus in Markov Chain Monte Carlo-Based Bayesian Analyses", Genetics, vol.167, issue.2, p.1037, 2004.
DOI : 10.1534/genetics.103.025320

C. Andrieu, P. M. Djuri´cdjuri´c, and A. Doucet, Model selection by MCMC computation, Signal Processing, vol.81, issue.1, pp.19-37, 2001.
DOI : 10.1016/S0165-1684(00)00188-2