Learning stochastic dynamical systems with neural networks mimicking the Euler-Maruyama scheme

Mapping Intimacies ◽

10.23919/eusipco54536.2021.9616068 ◽

2021 ◽

Author(s):

Naura Dridi ◽

Lucas Drumetz ◽

Ronan Fablet

Keyword(s):

Neural Networks ◽

Dynamical Systems ◽

Stochastic Dynamical Systems

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Coherent phenomena in stochastic dynamical systems

Uspekhi Fizicheskih Nauk ◽

10.3367/ufnr.0169.199902c.0171 ◽

1999 ◽

Vol 169 (2) ◽

pp. 171 ◽

Author(s):

Valerii I. Klyatskin ◽

D. Gurarie

Keyword(s):

Dynamical Systems ◽

Stochastic Dynamical Systems

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SURROGATE MODELING FOR STOCHASTIC DYNAMICAL SYSTEMS BY COMBINING NONLINEAR AUTOREGRESSIVE WITH EXOGENOUS INPUT MODELS AND POLYNOMIAL CHAOS EXPANSIONS

International Journal for Uncertainty Quantification ◽

10.1615/int.j.uncertaintyquantification.2016016603 ◽

2016 ◽

Vol 6 (4) ◽

pp. 313-339 ◽

Author(s):

Chu V. Mai ◽

Minas D. Spiridonakos ◽

Eleni N. Chatzi ◽

Bruno Sudret

Keyword(s):

Dynamical Systems ◽

Polynomial Chaos ◽

Surrogate Modeling ◽

Stochastic Dynamical Systems ◽

Polynomial Chaos Expansions ◽

Nonlinear Autoregressive

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On the effects of non-linear elements in the reliability-based optimal design of stochastic dynamical systems

International Journal of Non-Linear Mechanics ◽

10.1016/j.ijnonlinmec.2007.03.003 ◽

2007 ◽

Vol 42 (5) ◽

pp. 802-816 ◽

Author(s):

Hector A. Jensen ◽

Michel A. Catalan

Keyword(s):

Dynamical Systems ◽

Optimal Design ◽

Stochastic Dynamical Systems ◽

Linear Elements

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Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems

IEEE Transactions on Neural Networks ◽

10.1109/72.392253 ◽

1995 ◽

Vol 6 (4) ◽

pp. 911-917 ◽

Author(s):

Tianping Chen ◽

Hong Chen

Keyword(s):

Neural Networks ◽

Dynamical Systems ◽

Universal Approximation ◽

Activation Functions ◽

Nonlinear Operators

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A remark on symmetry of stochastic dynamical systems and their conserved quantities

Journal of Physics A General Physics ◽

10.1088/0305-4470/28/22/012 ◽

1995 ◽

Vol 28 (22) ◽

pp. 6363-6371 ◽

Author(s):

S Albeverio ◽

Shao-Ming Fei

Keyword(s):

Dynamical Systems ◽

Conserved Quantities ◽

Stochastic Dynamical Systems

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Global identification of stochastic dynamical systems under different pseudo-static operating conditions: The functionally pooled ARMAX case

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2016.05.002 ◽

2017 ◽

Vol 82 ◽

pp. 32-55 ◽

Author(s):

J.S. Sakellariou ◽

S.D. Fassois

Keyword(s):

Dynamical Systems ◽

Operating Conditions ◽

Stochastic Dynamical Systems ◽

Global Identification

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Quantitative stability estimates for multiscale stochastic dynamical systems

Statistics & Probability Letters ◽

10.1016/j.spl.2021.109193 ◽

2021 ◽

pp. 109193

Author(s):

Junyu Guo ◽

Xiaotian Guo ◽

Longjie Xie

Keyword(s):

Dynamical Systems ◽

Stability Estimates ◽

Stochastic Dynamical Systems ◽

Quantitative Stability

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Nonlinear-nonquadratic optimal and inverse optimal control for stochastic dynamical systems

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.3829 ◽

2017 ◽

Vol 27 (18) ◽

pp. 4723-4751 ◽

Author(s):

Tanmay Rajpurohit ◽

Wassim M. Haddad

Keyword(s):

Optimal Control ◽

Dynamical Systems ◽

Inverse Optimal Control ◽

Stochastic Dynamical Systems

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Nonlinear reduction of high-dimensional dynamical systems via neural networks

Physical Review Letters ◽

10.1103/physrevlett.72.1822 ◽

1994 ◽

Vol 72 (12) ◽

pp. 1822-1825 ◽

Author(s):

Michael Kirby ◽

Rick Miranda

Keyword(s):

Neural Networks ◽

Dynamical Systems ◽

High Dimensional

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A Statistical Approach for Computing Reachability of Non-linear and Stochastic Dynamical Systems

Quantitative Evaluation of Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-319-10696-0_5 ◽

2014 ◽

pp. 41-56 ◽

Author(s):

Luca Bortolussi ◽

Guido Sanguinetti

Keyword(s):

Dynamical Systems ◽

Statistical Approach ◽

Stochastic Dynamical Systems ◽

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