Homogeneous spiking neural P systems working in sequential mode induced by maximum spike number

Abstract

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes, where neurons work in parallel in the sense that each neuron that can fire should fire at each computation step, and neurons can be different in the sense that they can have different sets of spiking rules. In this work, we consider SN P systems with the restrictions: (1) all neurons are homogeneous in the sense that each neuron has the same set of rules; (2) at each step the neuron with the maximum number of spikes among the neurons that are active (can spike) will fire. These restrictions correspond to the fact that the system consists of only one kind of neurons and a global view of the whole network makes the system sequential. The computation power of homogeneous SN P systems working in the sequential mode induced by the maximum spike number is investigated. Specifically, it is proved that such systems are universal as both generating and accepting devices.

Keywords:

• membrane computing
• spiking neural P system
• homogeneity
• sequential mode
• turing completeness

2010 AMS Subject Classification:

• 68Q05

Acknowledgements

This work was supported by National Natural Science Foundation of China (61033003, 91130034 and 30870826), PhD Programs Foundation of Ministry of Education of China (20100142110072), Fundamental Research Funds for the Central Universities (2011TS005 and 2011TS006) and Natural Science Foundation of Hubei Province (2011CDA027).