Asynchronous Spiking Neural P Systems With Rules Working in the Rule Synchronization Mode

Abstract

Asynchronous spiking neural P systems with rules on synapses (ARSSN P systems) are a class of computation models, where spiking rules are placed on synapses. In this work, we investigate the computation power of ARSSN P systems working in the rule synchronization mode, where a family of rule sets are specified, and all the rules in a such set should be synchronously used or not. We prove that ARSSN P systems working in the rule synchronization mode are universal as number generating. Additionally, two universal ARSSN P systems working in the rule synchronization mode are constructed to accept numbers and compute functions, respectively. The results indicate that rule synchronization set is a powerful ingredient for resource-saving, as the constructed universal ARSSN P systems with rule synchronization sets use less neurons than the counterpart universal systems without such sets.