@article {986,
title = {Small universal simple Spiking Neural P Systems with weights},
journal = {Science China. Information Sciences},
volume = {57},
year = {2014},
pages = {1-11},
publisher = {Springer},
address = {Beijing, China},
abstract = {Spiking neural P systems with weights (WSN P systems, for short) are a new variant of spiking neural P systems, where the rules of a neuron are enabled when the potential of that neuron equals a given value. It is known that WSN P systems are universal by simulating register machines. However, in these universal systems, no bound is considered on the number of neurons and rules. In this work, a restricted variant of WSN P systems is considered, called simple WSN P systems, where each neuron has only one rule. The complexity parameter, the number of neurons, to construct a universal simple WSN P system is investigated. It is proved that there is a universal simple WSN P system with 48 neurons for computing functions; as generator of sets of numbers, there is an almost simple (that is, each neuron has only one rule except that one neuron has two rules) and universal WSN P system with 45 neurons.},
keywords = {bio-inspired computing, Membrane computing, P system, Spiking neural P system, universal computing device},
issn = {1674-733X},
doi = {10.1007/s11432-013-4848-z},
url = {http://link.springer.com/article/10.1007\%2Fs11432-013-4848-z},
author = {XiangXiang Zeng and Linqiang Pan and Mario J. P{\'e}rez-Jim{\'e}nez}
}