Spiking neural P systems with neuron permeability

Spiking neural P systems (SNP systems) are a class of distributed parallel and interpretable computing models developed in recent years, which are abstracted from the mechanism of spiking neurons and the nervous system. At present, the development of SNP variants has become a hot spot. To enhance the plasticity of SNP systems, inspired by the biological neural mechanism of the variable permeability of neurons, spiking neural P systems with neuron permeability (NP-SNP systems) are discovered and proposed as a novel variant of SNP systems. In NP-SNP systems, neurons have variable permeability directly related to membrane thickness. Membrane permeability changes with the change of membrane thickness. The proposed permeability spike rules are used to quantify changes in permeability. A specific NP-SNP system for generating arbitrary natural numbers is constructed. It is proved that the computing power of NP-SNP systems possesses Turing universality from number-generation, number-acceptance and computing functions. Devoted to the NP-complete problem, the NP-SNP system deterministically solves the Subset Sum problem in linear time. Compared with five variants, NP-SNP systems show advantages in less time steps and deterministic solutions.