Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

Xiaokai Nie; Jingjing Luo; Daniel Coca; Mark Birkin; Jing Chen

doi:10.1007/s00332-018-9455-0

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

Xiaokai Nie, Jingjing Luo, Daniel Coca, Mark Birkin, Jing Chen

Research output: Contribution to journal › Article › peer-review

Abstract

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

Original language	English
Journal	Journal of Nonlinear Science
Early online date	21 Mar 2018
DOIs	https://doi.org/10.1007/s00332-018-9455-0
Publication status	Published - 2018

Keywords

Nonlinear systems Probability density functions Frobenius–Perron operator Stochastic dynamical systems

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10.1007/s00332-018-9455-0

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@article{181c718e09f04bf997f1d9388b79ee53,

title = "Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions",

abstract = "The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.",

keywords = "Nonlinear systems Probability density functions Frobenius–Perron operator Stochastic dynamical systems",

author = "Xiaokai Nie and Jingjing Luo and Daniel Coca and Mark Birkin and Jing Chen",

year = "2018",

doi = "10.1007/s00332-018-9455-0",

language = "English",

journal = "Journal of Nonlinear Science",

issn = "0938-8974",

publisher = "Springer Nature",

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T1 - Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

AU - Nie, Xiaokai

AU - Luo, Jingjing

AU - Coca, Daniel

AU - Birkin, Mark

AU - Chen, Jing

PY - 2018

Y1 - 2018

N2 - The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

AB - The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

KW - Nonlinear systems Probability density functions Frobenius–Perron operator Stochastic dynamical systems

U2 - 10.1007/s00332-018-9455-0

DO - 10.1007/s00332-018-9455-0

M3 - Article

SN - 0938-8974

JO - Journal of Nonlinear Science

JF - Journal of Nonlinear Science

ER -

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

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