On String Languages Generated by Spiking Neural P Systems with Multiple Channels

Abstract

We study spiking neural P system with multiple channels (SNP-MC), where each neuron can be connected to several subsets of neurons. Turing universality of SNP-MC systems as number generating/accepting devices and function computing devices has been already proven. However, a universality result of SNP-MC systems as language generators has not been established so far. This paper discusses computation power of SNP-MC systems as language generators. We prove that recursively enumerable languages can be characterized as projections of inverse-morphic images of languages generated by SNP-MC systems. The relationships of languages generated by SNP-MC systems with finite and regular languages are also investigated.

Master Student in Deep Learning

I am a master student of artificial intelligence at the Xihua University. My research includes machine learning, deep learning, computer vision.