Paper Info
Title
Asynchronous homogenous spiking neural P systems with local rule synchronization
Abstract
Homogenous spiking neural P systems (HSNP systems) are a class of neuron-inspired computing models, where each neuron contains an identical set of rules. It remains open how to design universal asynchronous HSNP systems. In this work, we introduce local rule synchronization into asynchronous HSNP systems, and such systems are abbreviated as AHSNPR systems. Specifically, a family of the rule sets is specified; a rule in a specified rule set is applied synchronously with all the other rules in the same set, and a rule not in any specified rule set is applied asynchronously. We investigate the number generating power of AHSNPR systems. It is proved that general and unbounded AHSNPR systems are universal, and bounded AHSNPR systems are only able to characterize the semilinear sets of numbers achieving the corresponding properties of decidability and closure. The results show that the local rule synchronization is useful in constructing universal asynchronous HSNP systems.
Year
DOI
Venue
2022
10.1016/j.tcs.2022.05.023
Theoretical Computer Science
Keywords
DocType
Volume
Bio-inspired computing,Membrane computing,Spiking neural P system,Homogenous neuron,Asynchronous mode,Rule synchronization
Journal
926
ISSN
Citations 
PageRank 
0304-3975
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Luping Zhang100.34
Fei Xu201.01