A Gaussian Mixture Model Smoother for Continuous Nonlinear Stochastic Dynamical Systems: Applications
The nonlinear Gaussian Mixture Model Dynamically Orthogonal (GMM-DO) smoother for high-dimensional stochastic fields is exemplified and contrasted with other smoothers by applications to three dynamical systems, all of which admit far-from-Gaussian distributions. The capabilities of the smoother are...
Main Authors: | Lermusiaux, Pierre, Lolla, Tapovan |
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Other Authors: | Massachusetts Institute of Technology. Department of Mechanical Engineering |
Format: | Article |
Published: |
American Meteorological Society
2018
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Online Access: | http://hdl.handle.net/1721.1/114644 https://orcid.org/0000-0002-1869-3883 |
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