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Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty
In this paper, the authors outline the general principles behind an approach to Bayesian system identification and highlight the benefits of adopting a Bayesian framework when attempting to identify models of nonlinear dynamical systems in the presence of uncertainty. It is then described how, throu...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society Publishing
2015
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549940/ https://www.ncbi.nlm.nih.gov/pubmed/26303916 http://dx.doi.org/10.1098/rsta.2014.0405 |