Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework

The brain possesses the remarkable ability to seamlessly integrate perception with decision making within a dynamically changing environment in a fault-tolerant, end-to-end manner. This extraordinary capability offers a compelling solution for brain-inspired intelligence, replete with the advantages...

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Detalles Bibliográficos
Autores: Yang, Shuangming, Wang, Haowen, Pang, Yanwei, Jin, Yaochu, Linares-Barranco, Bernabé
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2023
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/390736
Acceso en línea:http://hdl.handle.net/10261/390736
https://api.elsevier.com/content/abstract/scopus_id/85177085847
Access Level:acceso abierto
Palabra clave:Decision making
Fault tolerant
Neuromorphic computing
Spike-timing-dependent plasticity (STDP)
Spiking neural network (SNN)
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spelling Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning FrameworkYang, ShuangmingWang, HaowenPang, YanweiJin, YaochuLinares-Barranco, BernabéDecision makingFault tolerantNeuromorphic computingSpike-timing-dependent plasticity (STDP)Spiking neural network (SNN)The brain possesses the remarkable ability to seamlessly integrate perception with decision making within a dynamically changing environment in a fault-tolerant, end-to-end manner. This extraordinary capability offers a compelling solution for brain-inspired intelligence, replete with the advantages of end-to-end decision making: robustness, high accuracy, real-time responsiveness, autonomous intelligence, and a high degree of biological plausibility. Neuromorphic computing stands as a promising avenue for brain-inspired intelligence through the harmonious co-design of algorithms and hardware, aimed at unlocking full potential. This article introduces a comprehensive neuromorphic computing framework for end-to-end intelligence. It introduces the quadruplet spike-timing-dependent plasticity, which serves as a cornerstone for perceptual to decision-making tasks. A fault-tolerant neuromorphic routing strategy is presented to fortify the framework's robustness. Empirical results underscore its impressive attributes with high accuracy, robustness, fault tolerance, and minimal computational latency when orchestrating end-to-end decision-making alongside visual perception. This study marks a pioneering effort in unified, fault-tolerant neuromorphic framework engineered for brain-inspired end-to-end intelligent tasks, merging visual perception with adaptive decision making. Such an endeavor is profoundly meaningful, as it propels the development of artificial general intelligence, holding vast implications for the field's advancement.This work was supported partly by the National Key Research and Development Program of China (Grant No. 2022ZD0160405), and partly by the National Natural Science Foundation of China (Grant No.62376185, and 62176179)Peer reviewedInstitute of Electrical and Electronics EngineersNational Natural Science Foundation of ChinaYang, Shuangming [0000-0002-8044-0860]Pang, Yanwei [0000-0001-6670-3727]Jin, Yaochu [0000-0003-1100-0631]Linares-Barranco, Bernabé [0000-0002-1813-4889]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252023info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://hdl.handle.net/10261/390736https://api.elsevier.com/content/abstract/scopus_id/85177085847reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1109/TSMC.2023.3327142Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3907362026-05-22T06:33:51Z
dc.title.none.fl_str_mv Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
title Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
spellingShingle Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
Yang, Shuangming
Decision making
Fault tolerant
Neuromorphic computing
Spike-timing-dependent plasticity (STDP)
Spiking neural network (SNN)
title_short Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
title_full Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
title_fullStr Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
title_full_unstemmed Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
title_sort Integrating Visual Perception With Decision Making in Neuromorphic Fault-Tolerant Quadruplet-Spike Learning Framework
dc.creator.none.fl_str_mv Yang, Shuangming
Wang, Haowen
Pang, Yanwei
Jin, Yaochu
Linares-Barranco, Bernabé
author Yang, Shuangming
author_facet Yang, Shuangming
Wang, Haowen
Pang, Yanwei
Jin, Yaochu
Linares-Barranco, Bernabé
author_role author
author2 Wang, Haowen
Pang, Yanwei
Jin, Yaochu
Linares-Barranco, Bernabé
author2_role author
author
author
author
dc.contributor.none.fl_str_mv National Natural Science Foundation of China
Yang, Shuangming [0000-0002-8044-0860]
Pang, Yanwei [0000-0001-6670-3727]
Jin, Yaochu [0000-0003-1100-0631]
Linares-Barranco, Bernabé [0000-0002-1813-4889]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Decision making
Fault tolerant
Neuromorphic computing
Spike-timing-dependent plasticity (STDP)
Spiking neural network (SNN)
topic Decision making
Fault tolerant
Neuromorphic computing
Spike-timing-dependent plasticity (STDP)
Spiking neural network (SNN)
description The brain possesses the remarkable ability to seamlessly integrate perception with decision making within a dynamically changing environment in a fault-tolerant, end-to-end manner. This extraordinary capability offers a compelling solution for brain-inspired intelligence, replete with the advantages of end-to-end decision making: robustness, high accuracy, real-time responsiveness, autonomous intelligence, and a high degree of biological plausibility. Neuromorphic computing stands as a promising avenue for brain-inspired intelligence through the harmonious co-design of algorithms and hardware, aimed at unlocking full potential. This article introduces a comprehensive neuromorphic computing framework for end-to-end intelligence. It introduces the quadruplet spike-timing-dependent plasticity, which serves as a cornerstone for perceptual to decision-making tasks. A fault-tolerant neuromorphic routing strategy is presented to fortify the framework's robustness. Empirical results underscore its impressive attributes with high accuracy, robustness, fault tolerance, and minimal computational latency when orchestrating end-to-end decision-making alongside visual perception. This study marks a pioneering effort in unified, fault-tolerant neuromorphic framework engineered for brain-inspired end-to-end intelligent tasks, merging visual perception with adaptive decision making. Such an endeavor is profoundly meaningful, as it propels the development of artificial general intelligence, holding vast implications for the field's advancement.
publishDate 2023
dc.date.none.fl_str_mv 2023
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/390736
https://api.elsevier.com/content/abstract/scopus_id/85177085847
url http://hdl.handle.net/10261/390736
https://api.elsevier.com/content/abstract/scopus_id/85177085847
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1109/TSMC.2023.3327142
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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