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Path Integral Methods for Stochastic Differential Equations
Stochastic differential equations (SDEs) have multiple applications in mathematical neuroscience and are notoriously difficult. Here, we give a self-contained pedagogical review of perturbative field theoretic and path integral methods to calculate moments of the probability density function of SDEs...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385267/ https://www.ncbi.nlm.nih.gov/pubmed/25852983 http://dx.doi.org/10.1186/s13408-015-0018-5 |
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author | Chow, Carson C. Buice, Michael A. |
author_facet | Chow, Carson C. Buice, Michael A. |
author_sort | Chow, Carson C. |
collection | PubMed |
description | Stochastic differential equations (SDEs) have multiple applications in mathematical neuroscience and are notoriously difficult. Here, we give a self-contained pedagogical review of perturbative field theoretic and path integral methods to calculate moments of the probability density function of SDEs. The methods can be extended to high dimensional systems such as networks of coupled neurons and even deterministic systems with quenched disorder. |
format | Online Article Text |
id | pubmed-4385267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-43852672015-04-07 Path Integral Methods for Stochastic Differential Equations Chow, Carson C. Buice, Michael A. J Math Neurosci Research Stochastic differential equations (SDEs) have multiple applications in mathematical neuroscience and are notoriously difficult. Here, we give a self-contained pedagogical review of perturbative field theoretic and path integral methods to calculate moments of the probability density function of SDEs. The methods can be extended to high dimensional systems such as networks of coupled neurons and even deterministic systems with quenched disorder. Springer Berlin Heidelberg 2015-03-24 /pmc/articles/PMC4385267/ /pubmed/25852983 http://dx.doi.org/10.1186/s13408-015-0018-5 Text en © Chow and Buice; licensee Springer. 2015 Open Access This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Research Chow, Carson C. Buice, Michael A. Path Integral Methods for Stochastic Differential Equations |
title | Path Integral Methods for Stochastic Differential Equations |
title_full | Path Integral Methods for Stochastic Differential Equations |
title_fullStr | Path Integral Methods for Stochastic Differential Equations |
title_full_unstemmed | Path Integral Methods for Stochastic Differential Equations |
title_short | Path Integral Methods for Stochastic Differential Equations |
title_sort | path integral methods for stochastic differential equations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385267/ https://www.ncbi.nlm.nih.gov/pubmed/25852983 http://dx.doi.org/10.1186/s13408-015-0018-5 |
work_keys_str_mv | AT chowcarsonc pathintegralmethodsforstochasticdifferentialequations AT buicemichaela pathintegralmethodsforstochasticdifferentialequations |