Bayesian Segmentation in Signal with Multiplicative Noise Using Reversible Jump MCMC

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Summary

The Reversible Jump Markov chain Monte Carlo (MCMC) method is adopted to overcome the problem of signal segmentation where the signal is disturbed by multiplicative noise where the number of segments is unknown.

Type
article
Published
2018-04-01
Cited by
5
References
12
Access
Open access

Keywords

Markov chain Monte Carlo, Reversible-jump Markov chain Monte Carlo, Bayesian probability, Algorithm, Posterior probability

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