A sequential importance sampling filter with a new proposal distribution for state and parameter estimation of nonlinear dynamical systems
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Publication:5438174
DOI10.1098/rspa.2007.0075zbMath1132.81006OpenAlexW1969880327WikidataQ60585185 ScholiaQ60585185MaRDI QIDQ5438174
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Publication date: 23 January 2008
Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1098/rspa.2007.0075
Gaussian processes (60G15) Estimation and detection in stochastic control theory (93E10) Diffusion processes (60J60) Asymptotic properties of parametric tests (62F05)
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Nonlinear filters for chaotic oscillatory systems ⋮ Joint maximum \textit{a posteriori} state path and parameter estimation in stochastic differential equations ⋮ Uncertainty estimation in equality-constrained MAP and maximum likelihood estimation with applications to system identification and state estimation ⋮ A pseudo-dynamical systems approach to a class of inverse problems in engineering ⋮ Self-regularized pseudo time-marching schemes for structural system identification with static measurements ⋮ The use of polynomial chaos for parameter identification from measurements in nonlinear dynamical systems ⋮ A Bayes estimator of parameters of nonlinear dynamic systems
Cites Work
- Monte Carlo filters for identification of nonlinear structural dynamical systems
- New forms of extended Kalman filter via transversal linearization and applications to structural system identification
- Use of particle filters in an active control algorithm for noisy nonlinear structural dynamical systems
- Higher order weak linearizations of stochastically driven nonlinear oscillators
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