Optimum Integration Procedure for Connectionist and Dynamic Field Equations

Autores
Rieznik, Andrés Anibal; Di Tella, Rocco; Schvartzman, Lara; Babino, Andrés
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler method, and two methods we have developed and present here: a modified version of the fourth-order Runge Kutta method, and one semi-analytical method. We apply them to solve a well-known nonlinear connectionist model of retrieval in single-digit multiplication, and show that, in many regimes, the semi-analytical and modified Runge Kutta methods outperform the Euler method, in some regimes by more than three orders of magnitude. Given the outstanding difference in execution time of the methods, and that the EM is widely used, we conclude that the researchers in the field can greatly benefit from our analysis and developed methods.
Fil: Rieznik, Andrés Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina
Fil: Di Tella, Rocco. Universidad de Buenos Aires; Argentina
Fil: Schvartzman, Lara. Universidad de Buenos Aires; Argentina
Fil: Babino, Andrés. The Rockefeller University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
COGNITIVE MODELS
COGNITIVE NEUROSCIENCE
CONNECTIONISM AND NEURAL NETS
NEUROROBOTIC
NUMERICAL OPTIMISATION TECHNIQUES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/171869

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network_name_str CONICET Digital (CONICET)
spelling Optimum Integration Procedure for Connectionist and Dynamic Field EquationsRieznik, Andrés AnibalDi Tella, RoccoSchvartzman, LaraBabino, AndrésCOGNITIVE MODELSCOGNITIVE NEUROSCIENCECONNECTIONISM AND NEURAL NETSNEUROROBOTICNUMERICAL OPTIMISATION TECHNIQUEShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler method, and two methods we have developed and present here: a modified version of the fourth-order Runge Kutta method, and one semi-analytical method. We apply them to solve a well-known nonlinear connectionist model of retrieval in single-digit multiplication, and show that, in many regimes, the semi-analytical and modified Runge Kutta methods outperform the Euler method, in some regimes by more than three orders of magnitude. Given the outstanding difference in execution time of the methods, and that the EM is widely used, we conclude that the researchers in the field can greatly benefit from our analysis and developed methods.Fil: Rieznik, Andrés Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; ArgentinaFil: Di Tella, Rocco. Universidad de Buenos Aires; ArgentinaFil: Schvartzman, Lara. Universidad de Buenos Aires; ArgentinaFil: Babino, Andrés. The Rockefeller University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFrontiers Media2021-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/171869Rieznik, Andrés Anibal; Di Tella, Rocco; Schvartzman, Lara; Babino, Andrés; Optimum Integration Procedure for Connectionist and Dynamic Field Equations; Frontiers Media; Frontiers in Neurorobotics; 15; 5-2021; 1-61662-5218CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fnbot.2021.670895info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnbot.2021.670895/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:47Zoai:ri.conicet.gov.ar:11336/171869instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:53:47.903CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimum Integration Procedure for Connectionist and Dynamic Field Equations
title Optimum Integration Procedure for Connectionist and Dynamic Field Equations
spellingShingle Optimum Integration Procedure for Connectionist and Dynamic Field Equations
Rieznik, Andrés Anibal
COGNITIVE MODELS
COGNITIVE NEUROSCIENCE
CONNECTIONISM AND NEURAL NETS
NEUROROBOTIC
NUMERICAL OPTIMISATION TECHNIQUES
title_short Optimum Integration Procedure for Connectionist and Dynamic Field Equations
title_full Optimum Integration Procedure for Connectionist and Dynamic Field Equations
title_fullStr Optimum Integration Procedure for Connectionist and Dynamic Field Equations
title_full_unstemmed Optimum Integration Procedure for Connectionist and Dynamic Field Equations
title_sort Optimum Integration Procedure for Connectionist and Dynamic Field Equations
dc.creator.none.fl_str_mv Rieznik, Andrés Anibal
Di Tella, Rocco
Schvartzman, Lara
Babino, Andrés
author Rieznik, Andrés Anibal
author_facet Rieznik, Andrés Anibal
Di Tella, Rocco
Schvartzman, Lara
Babino, Andrés
author_role author
author2 Di Tella, Rocco
Schvartzman, Lara
Babino, Andrés
author2_role author
author
author
dc.subject.none.fl_str_mv COGNITIVE MODELS
COGNITIVE NEUROSCIENCE
CONNECTIONISM AND NEURAL NETS
NEUROROBOTIC
NUMERICAL OPTIMISATION TECHNIQUES
topic COGNITIVE MODELS
COGNITIVE NEUROSCIENCE
CONNECTIONISM AND NEURAL NETS
NEUROROBOTIC
NUMERICAL OPTIMISATION TECHNIQUES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler method, and two methods we have developed and present here: a modified version of the fourth-order Runge Kutta method, and one semi-analytical method. We apply them to solve a well-known nonlinear connectionist model of retrieval in single-digit multiplication, and show that, in many regimes, the semi-analytical and modified Runge Kutta methods outperform the Euler method, in some regimes by more than three orders of magnitude. Given the outstanding difference in execution time of the methods, and that the EM is widely used, we conclude that the researchers in the field can greatly benefit from our analysis and developed methods.
Fil: Rieznik, Andrés Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina
Fil: Di Tella, Rocco. Universidad de Buenos Aires; Argentina
Fil: Schvartzman, Lara. Universidad de Buenos Aires; Argentina
Fil: Babino, Andrés. The Rockefeller University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler method, and two methods we have developed and present here: a modified version of the fourth-order Runge Kutta method, and one semi-analytical method. We apply them to solve a well-known nonlinear connectionist model of retrieval in single-digit multiplication, and show that, in many regimes, the semi-analytical and modified Runge Kutta methods outperform the Euler method, in some regimes by more than three orders of magnitude. Given the outstanding difference in execution time of the methods, and that the EM is widely used, we conclude that the researchers in the field can greatly benefit from our analysis and developed methods.
publishDate 2021
dc.date.none.fl_str_mv 2021-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/171869
Rieznik, Andrés Anibal; Di Tella, Rocco; Schvartzman, Lara; Babino, Andrés; Optimum Integration Procedure for Connectionist and Dynamic Field Equations; Frontiers Media; Frontiers in Neurorobotics; 15; 5-2021; 1-6
1662-5218
CONICET Digital
CONICET
url http://hdl.handle.net/11336/171869
identifier_str_mv Rieznik, Andrés Anibal; Di Tella, Rocco; Schvartzman, Lara; Babino, Andrés; Optimum Integration Procedure for Connectionist and Dynamic Field Equations; Frontiers Media; Frontiers in Neurorobotics; 15; 5-2021; 1-6
1662-5218
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fnbot.2021.670895
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnbot.2021.670895/full
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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