A normal form of spiking neural P systems with structural plasticity Online publication date: Fri, 06-Nov-2015
by Tao Song; Linqiang Pan
International Journal of Swarm Intelligence (IJSI), Vol. 1, No. 4, 2015
Abstract: Spiking neural P systems (SN P systems, in short) are a class of distributed and parallel neural-like computing models, which are inspired by the way of biological neurons processing information and communication by means of impulses (or spikes). SN P systems with structural plasticity are a new variant of SN P systems, which have plasticity to the topological structure in the sense that connections among neurons can be reformed by creating and deleting synapses during the computation. In this work, we give a normal form of universal SN P systems with structural plasticity. Specifically, we prove that SN P systems with structural plasticity can achieve Turing universality with the restriction that any neuron can either create or delete synapses, instead of both, in a computation step. This result gives an answer to an open problem formulated in Francis et al. (2013).
Online publication date: Fri, 06-Nov-2015
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