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Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification
A conditional Gaussian framework for understanding and predicting complex multiscale nonlinear stochastic systems is developed. Despite the conditional Gaussianity, such systems are nevertheless highly nonlinear and are able to capture the non-Gaussian features of nature. The special structure of th...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513031/ https://www.ncbi.nlm.nih.gov/pubmed/33265599 http://dx.doi.org/10.3390/e20070509 |