- Title
- Parallel MCMC algorithm for Bayesian system identification
- Creator
- Tran, Khoa T.; Ninness, Brett
- Relation
- 2015 54th IEEE Conference on Decision and Control (CDC). Proceedings of the 2015 54th IEEE Conference on Decision and Control (CDC) (Osaka, Japan 15-18 December, 2015) p. 2438-2443
- Publisher Link
- http://dx.doi.org/10.1109/CDC.2015.7402573
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2016
- Description
- A generalised framework for Metropolis-Hastings admits many algorithms as specialisations and allows for synthesis of multiple methods to create a parallel algorithm, with no tuning required, to efficiently draw uncorrelated samples, from the posterior density in Bayesian systems identification, at lower computational cost in comparison with conventional samplers. Two automatic annealing schemes demonstrate complementary robustness in detecting multi-modal distribution.
- Subject
- simulated annealing; Bayes methods; identification; Markov processes; Monte Carlo methods; parallel algorithms
- Identifier
- http://hdl.handle.net/1959.13/1318606
- Identifier
- uon:23652
- Identifier
- ISBN:9781479978861
- Language
- eng
- Reviewed
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