Bayesian reconstructions and predictions of nonlinear dynamical systems via the hybrid Monte Carlo scheme

Signal Processing ◽

10.1016/j.sigpro.2004.09.007 ◽

2005 ◽

Vol 85 (1) ◽

pp. 129-145 ◽

Author(s):

Yohei Nakada ◽

Takashi Matsumoto ◽

Takayuki Kurihara ◽

Kuniaki Yosui

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Hybrid Monte Carlo ◽

Nonlinear Dynamical

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Discrepancy Driven Adaptive Monte Carlo for Forward Uncertainty Forecasting in Nonlinear Dynamical Systems

2018 Annual American Control Conference (ACC) ◽

10.23919/acc.2018.8431731 ◽

2018 ◽

Author(s):

Chao Yang ◽

Mrinal Kumar

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Nonlinear Dynamical ◽

Adaptive Monte Carlo

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Reconstructions and predictions of nonlinear dynamical systems by Rao-Blackwellised sequential Monte Carlo

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). ◽

10.1109/icassp.2003.1202482 ◽

2003 ◽

Author(s):

T. Soma ◽

K. Yosui ◽

T. Matsumoto

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Sequential Monte Carlo ◽

Nonlinear Dynamical Systems ◽

Nonlinear Dynamical

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Monte Carlo Gaussian Sum Filter For State Estimation of Nonlinear Dynamical Systems∗∗The authors would like to thank Dept. of Science and Technology for partially funding this research under the grant 13DST057.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2016.03.030 ◽

2016 ◽

Vol 49 (1) ◽

pp. 65-70

Author(s):

Krishna Kumar Kottakki ◽

Mani Bhushan ◽

Sharad Bhartiya

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

State Estimation ◽

Nonlinear Dynamical Systems ◽

Science And Technology ◽

Nonlinear Dynamical ◽

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On the effectiveness of Monte Carlo for initial uncertainty forecasting in nonlinear dynamical systems

10.1016/j.automatica.2017.09.025 ◽

2018 ◽

Vol 87 ◽

pp. 301-309 ◽

Author(s):

Chao Yang ◽

Mrinal Kumar

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Nonlinear Dynamical ◽

Initial Uncertainty

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Monte Carlo Approach for Fatigue and Damage Calculation of Nonlinear Dynamical Systems

PAMM ◽

10.1002/1617-7061(200203)1:1<460::aid-pamm460>3.0.co;2-f ◽

2002 ◽

Vol 1 (1) ◽

pp. 460

Author(s):

F. Poirion

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Nonlinear Dynamical ◽

Monte Carlo Approach

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Sequential Monte Carlo sampling in hidden Markov models of nonlinear dynamical systems

Applied Mathematics and Computation ◽

10.1016/j.amc.2014.02.012 ◽

2014 ◽

Vol 233 ◽

pp. 507-521 ◽

Author(s):

X. Zeng ◽

M. Anitescu

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Hidden Markov Models ◽

Sequential Monte Carlo ◽

Markov Models ◽

Nonlinear Dynamical Systems ◽

Hidden Markov ◽

Monte Carlo Sampling ◽

Nonlinear Dynamical

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Markov chain Monte Carlo (MCMC) method for parameter estimation of nonlinear dynamical systems

2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) ◽

10.1109/icsipa.2015.7412154 ◽

2015 ◽

Author(s):

M. Javvad ur Rehman ◽

Sarat Chandra Dass ◽

Vijanth Sagayan Asirvadam

Keyword(s):

Monte Carlo ◽

Parameter Estimation ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Mcmc Method ◽

Nonlinear Dynamical

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Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2017.10.033 ◽

2018 ◽

Vol 104 ◽

pp. 866-883 ◽

Author(s):

Thomas B. Schön ◽

Andreas Svensson ◽

Lawrence Murray ◽

Fredrik Lindsten

Keyword(s):

Monte Carlo ◽

Dynamical Systems ◽

Sequential Monte Carlo ◽

Nonlinear Dynamical Systems ◽

Probabilistic Learning ◽

Nonlinear Dynamical

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Noise in Nonlinear Dynamical Systems

10.1017/cbo9780511897825 ◽

1989 ◽

Keyword(s):

Dynamical Systems ◽

Nonlinear Dynamical Systems ◽

Nonlinear Dynamical

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Control Synthesis for Linear and Nonlinear Dynamical Systems under Bounded Measurement Errors of a State Vector

Journal of Automation and Information Sciences ◽

10.1615/jautomatinfscien.v48.i1.20 ◽

2016 ◽

Vol 48 (1) ◽

pp. 2-14

Author(s):

Vsevolod M. Kuntsevich

Keyword(s):

Dynamical Systems ◽

State Vector ◽

Measurement Errors ◽

Nonlinear Dynamical Systems ◽

Control Synthesis ◽

Nonlinear Dynamical ◽

Linear And Nonlinear

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