Computational completeness of sequential spiking neural P systems with autapses with partial synchronization

Spiking neural P systems with autapses (SNP-AU) are a novel variation of SN P systems, designed based on the autapses information transfer mechanism. All neurons are synchronized through a global clock, enabling the SNP-AU to operate in a synchronized mode. In this paper, we focus on studying the computational completeness of sequential SNP-AU with partial synchronization (SSNP-AU). The SSNP-AU has two sequential modes: the max-sequentiality and the max-pseudo-sequentiality strategies. It exhibits three unique and identifiable characteristics: (i) self-connection specificity of autapses; (ii) features local synchronization and automation in the state of the global sequence pattern; and (iii) the SNP-AU characteristics in sequential mode can efficiently simulate register instructions at a low cost. Furthermore, we have developed a small device for computing general functions, consisting of 65 neurons based on the SSNP-AU, which is utilized in the max-sequentiality strategy.