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dc.creatorPérez-Peña, Fernandoes
dc.creatorMorgado Estévez, Arturoes
dc.creatorLinares Barranco, Alejandroes
dc.date.accessioned2020-02-12T06:57:17Z
dc.date.available2020-02-12T06:57:17Z
dc.date.issued2015
dc.identifier.citationPérez-Peña, F., Morgado Estévez, A. y Linares Barranco, A. (2015). Inter-spikes-intervals exponential and gamma distributions study of neuron firing rate for SVITE motor control model on FPGA. Neurocomputing, 149, part B (February 2015), 496-504.
dc.identifier.issn0925-2312es
dc.identifier.urihttps://hdl.handle.net/11441/92904
dc.description.abstractThis paper presents a statistical study on a neuro-inspired spike-based implementation of the Vector-Integration-To-End-Point motor controller (SVITE) and compares its deterministic neuron-model stream of spikes with a proposed modification that converts the model, and thus the controller, in a Poisson like spike stream distribution. A set of hardware pseudo-random numbers generators, based on a Linear Feedback Shift Register (LFSR), have been introduced in the neuron-model so that they reach a closer biological neuron behavior. To validate the new neuron-model behavior a comparison between the Inter-Spikes-Interval empirical data and the Exponential and Gamma distributions has been carried out using the Kolmogorov–Smirnoff test. An in-hardware validation of the controller has been performed in a Spartan6 FPGA to drive directly with spikes DC motors from robotics to study the behavior and viability of the modified controller with random components. The results show that the original deterministic spikes distribution of the controller blocks can be swapped with Poisson distributions using 30-bit LFSRs. The comparative between the usable controlling signals such as the trajectory and the speed profile using a deterministic and the new controller show a standard deviation of 11.53 spikes/s and 3.86 spikes/s respectively. These rates do not affect our system because, within Pulse Frequency Modulation, in order to drive the motors, time length can be fixed to spread the spikes. Tuning this value, the slow rates could be filtered by the motor. Therefore, this SVITE neuro-inspired controller can be integrated within complex neuromorphic architectures with Poisson-like neurons.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofNeurocomputing, 149, part B (February 2015), 496-504.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBio-inspiredes
dc.subjectNeuro-inspiredes
dc.subjectAERes
dc.subjectLFSRes
dc.subjectPoissones
dc.subjectFPGAes
dc.titleInter-spikes-intervals exponential and gamma distributions study of neuron firing rate for SVITE motor control model on FPGAes
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadoreses
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0925231214010388es
dc.identifier.doi10.1016/j.neucom.2014.08.024es
dc.contributor.groupUniversidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitaciónes
idus.format.extent8es
dc.journaltitleNeurocomputinges
dc.publication.volumen149, part Bes
dc.publication.issueFebruary 2015es
dc.publication.initialPage496es
dc.publication.endPage504es
dc.identifier.sisius20724115es

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