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Asynchronous Spiking Neural P Systems with Structural Plasticity


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Author: Cabarle, Francis George C.
Adorna, Henry N.
Pérez Jiménez, Mario de Jesús
Department: Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Date: 2015
Published in: Proceedings of the Thirteenth Brainstorming Week on Membrane Computing, 91-104. Sevilla, E.T.S. de Ingeniería Informática, 2-6 de Febrero, 2015,
ISBN/ISSN: 978-84-944366-2-8
Document type: Presentation
Abstract: Spiking neural P (in short, SNP) systems are computing devices inspired by biological spiking neurons. In this work we consider SNP systems with structural plasticity (in short, SNPSP systems) working in the asynchronous (in short, asyn mode). SNPSP systems represent a class of SNP systems that have dynamic synapses, i.e. neurons can use plasticity rules to create or remove synapses. We prove that for asyn mode, bounded SNPSP systems (where any neuron produces at most one spike each step) are not universal, while unbounded SNPSP systems with weighted synapses (a weight associated with each synapse allows a neuron to produce more than one spike each step) are universal. The latter systems are similar to SNP systems with extended rules in asyn mode (known to be universal) while the former are similar to SNP systems with standard rules only in asyn mode (conjectured not to be universal). Our results thus provide support to the conjecture of the still open problem.
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