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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Acknowledgments
Cabarle is supported by a scholarship from the DOST-ERDT of the Philippines. Adorna is funded by a DOST-ERDT grant and the Semirara Mining Corp. Professorial Chair of the College of Engineering, UP Diliman. M.J. Pérez-Jiménez acknowledges the support of the Project TIN2012-37434 of the “Ministerio de Economía y Competitividad” of Spain, co-financed by FEDER funds. Anonymous referees are also acknowledged in helping improve this work.
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Cabarle, F.G.C., Adorna, H.N., Pérez-Jiménez, M.J. (2015). Asynchronous Spiking Neural P Systems with Structural Plasticity. In: Calude, C., Dinneen, M. (eds) Unconventional Computation and Natural Computation. UCNC 2015. Lecture Notes in Computer Science(), vol 9252. Springer, Cham. https://doi.org/10.1007/978-3-319-21819-9_9
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