A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems

The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density.

Detalles Bibliográficos
Autores principales: Nie, Xiaokai, Coca, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Center for Nonlinear Science, Peking University 2018
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5589148/
https://www.ncbi.nlm.nih.gov/pubmed/29299016
http://dx.doi.org/10.1016/j.cnsns.2017.05.011
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author Nie, Xiaokai
Coca, Daniel
author_facet Nie, Xiaokai
Coca, Daniel
author_sort Nie, Xiaokai
collection PubMed
description The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density.
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spelling pubmed-55891482018-01-01 A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems Nie, Xiaokai Coca, Daniel Commun Nonlinear Sci Numer Simul Research Paper The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density. Center for Nonlinear Science, Peking University 2018-01 /pmc/articles/PMC5589148/ /pubmed/29299016 http://dx.doi.org/10.1016/j.cnsns.2017.05.011 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Paper
Nie, Xiaokai
Coca, Daniel
A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title_full A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title_fullStr A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title_full_unstemmed A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title_short A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems
title_sort matrix-based approach to solving the inverse frobenius–perron problem using sequences of density functions of stochastically perturbed dynamical systems
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5589148/
https://www.ncbi.nlm.nih.gov/pubmed/29299016
http://dx.doi.org/10.1016/j.cnsns.2017.05.011
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AT cocadaniel amatrixbasedapproachtosolvingtheinversefrobeniusperronproblemusingsequencesofdensityfunctionsofstochasticallyperturbeddynamicalsystems
AT niexiaokai matrixbasedapproachtosolvingtheinversefrobeniusperronproblemusingsequencesofdensityfunctionsofstochasticallyperturbeddynamicalsystems
AT cocadaniel matrixbasedapproachtosolvingtheinversefrobeniusperronproblemusingsequencesofdensityfunctionsofstochasticallyperturbeddynamicalsystems

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