Notes on spiking neural P systems and finite automata

Spiking neural P systems (in short, SN P systems) are membrane computing models inspired by the pulse coding of information in biological neurons. SN P systems with standard rules have neurons that emit at most one spike (the pulse) each step, and have either an input or output neuron connected to t...

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Detalhes bibliográficos
Autores: Cabarle, Francis George C., Adorna, Henry N., Pérez Jiménez, Mario de Jesús
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/127847
Acesso em linha:https://hdl.handle.net/11441/127847
https://doi.org/10.1007/s11047-016-9563-4
Access Level:acceso abierto
Palavra-chave:Membrane computing
Spiking neural P system
Finite automata
Automatic sequence
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spelling Notes on spiking neural P systems and finite automataCabarle, Francis George C.Adorna, Henry N.Pérez Jiménez, Mario de JesúsMembrane computingSpiking neural P systemFinite automataAutomatic sequenceSpiking neural P systems (in short, SN P systems) are membrane computing models inspired by the pulse coding of information in biological neurons. SN P systems with standard rules have neurons that emit at most one spike (the pulse) each step, and have either an input or output neuron connected to the environment. A variant known as SN P modules generalize SN P systems by using extended rules (more than one spike can be emitted each step) and a set of input and output neurons. In this work we continue relating SN P modules and finite automata. In particular, we amend and improve previous constructions for the simulatons of deterministic finite automata and state transducers. Our improvements reduce the number of neurons from three down to one, so our results are optimal. We also simulate finite automata with output, and we use these simulations to generate automatic sequences.Ministerio de Economía y Competitividad TIN2012-37434SpringerCiencias de la Computación e Inteligencia ArtificialTIC193 : Computación NaturalMinisterio de Economía y Competitividad (MINECO). España2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/127847https://doi.org/10.1007/s11047-016-9563-4reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésNatural Computing, 15 (4), 533-539.TIN2012-37434https://link.springer.com/article/10.1007/s11047-016-9563-4info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1278472026-06-17T12:51:07Z
dc.title.none.fl_str_mv Notes on spiking neural P systems and finite automata
title Notes on spiking neural P systems and finite automata
spellingShingle Notes on spiking neural P systems and finite automata
Cabarle, Francis George C.
Membrane computing
Spiking neural P system
Finite automata
Automatic sequence
title_short Notes on spiking neural P systems and finite automata
title_full Notes on spiking neural P systems and finite automata
title_fullStr Notes on spiking neural P systems and finite automata
title_full_unstemmed Notes on spiking neural P systems and finite automata
title_sort Notes on spiking neural P systems and finite automata
dc.creator.none.fl_str_mv Cabarle, Francis George C.
Adorna, Henry N.
Pérez Jiménez, Mario de Jesús
author Cabarle, Francis George C.
author_facet Cabarle, Francis George C.
Adorna, Henry N.
Pérez Jiménez, Mario de Jesús
author_role author
author2 Adorna, Henry N.
Pérez Jiménez, Mario de Jesús
author2_role author
author
dc.contributor.none.fl_str_mv Ciencias de la Computación e Inteligencia Artificial
TIC193 : Computación Natural
Ministerio de Economía y Competitividad (MINECO). España
dc.subject.none.fl_str_mv Membrane computing
Spiking neural P system
Finite automata
Automatic sequence
topic Membrane computing
Spiking neural P system
Finite automata
Automatic sequence
description Spiking neural P systems (in short, SN P systems) are membrane computing models inspired by the pulse coding of information in biological neurons. SN P systems with standard rules have neurons that emit at most one spike (the pulse) each step, and have either an input or output neuron connected to the environment. A variant known as SN P modules generalize SN P systems by using extended rules (more than one spike can be emitted each step) and a set of input and output neurons. In this work we continue relating SN P modules and finite automata. In particular, we amend and improve previous constructions for the simulatons of deterministic finite automata and state transducers. Our improvements reduce the number of neurons from three down to one, so our results are optimal. We also simulate finite automata with output, and we use these simulations to generate automatic sequences.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/127847
https://doi.org/10.1007/s11047-016-9563-4
url https://hdl.handle.net/11441/127847
https://doi.org/10.1007/s11047-016-9563-4
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Natural Computing, 15 (4), 533-539.
TIN2012-37434
https://link.springer.com/article/10.1007/s11047-016-9563-4
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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