Spiking Neural P Systems With Multiple Channels And Symbols And Their Computational Completeness

Spiking neural P systems(SNP systems,in short)are a kind of distributed and parallel computing models,inspired by the way that neurons process and exchange information by means of spikes.This system provides a new non-traditional high-performance computing model and idea,so it is a hot topic in the field of membrane computing.A new variant of SNP systems is investigated in this paper,SNP systems with multiple channels and symbols(SNPMCS systems,in short).SNP-MCS systems have two interesting features: multiple channels and multiple symbols.That is,each neuron has more than one synaptic channel to connect its subsequent neurons,and there are multiple types of spikes in each neuron.The computational completeness of SNP-MCS systems,working in synchronous and asynchronous mode,is discussed.The innovative work of this paper is summarized as follows:(1)The spiking neural P systems with multiple channels and symbols(SNP-MCS systems for short)are proposed.(2)It is proved that SNP-MCS systems as number generating and accepting devices,working in synchronous mode,are Turing universal.At the same time,a SNP-MCS system with 103 neurons is constructed,which can be used as a small universal function computing device.(3)SNP-MCS systems in asynchronous mode(ASNP-MCS systems for short)are discussed.It is proved that ASNP-MCS systems as number generating devices,working in asynchronous mode,are Turing universal.At the same time,an ASNP-MCS system with 67 neurons is constructed,which can be used as a small universal function computing device.