Accurate state estimation of stiff continuous-time stochastic models in chemical and other engineering
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Publication:2229127
DOI10.1016/j.matcom.2017.04.006OpenAlexW2609899865MaRDI QIDQ2229127
Publication date: 19 February 2021
Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.matcom.2017.04.006
moment differential equationsstiff continuous-time stochastic systemstiff MDE solver with automatic local and global error controlsstochastic oregonator reaction model
Related Items (5)
Overall hyperbolic-singular-value-decomposition-based square-root solutions in Kalman filters with deterministically sampled mean and covariance for state estimation in continuous-discrete nonlinear stochastic systems ⋮ Nested implicit Runge-Kutta pairs of Gauss and Lobatto types with local and global error controls for stiff ordinary differential equations ⋮ Square-root filtering via covariance SVD factors in the accurate continuous-discrete extended-cubature Kalman filter ⋮ Itô-Taylor-based square-root unscented Kalman filtering methods for state estimation in nonlinear continuous-discrete stochastic systems ⋮ NIRK-based Cholesky-factorized square-root accurate continuous-discrete unscented Kalman filters for state estimation in nonlinear continuous-time stochastic models with discrete measurements
Uses Software
Cites Work
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