Research On Computational Power And Simulation Of Non-traditional Spiking Neural P Systems

In biocomputing,many high-performance computing models and intelligent algorithms are built on the characteristics of complex life activities.As a branch of biological computing,membrane computing is an efficient computing model which abstracts the structure,function and information interaction of biological cells.Spiking neural P systems is a computational model inspired by the mechanism of neurons transmitting information through spikes and they have been a research hotspot in the field of membrane computing.The present work mainly focuses on the research of the essential ingredients of spiking neural P systems,including the number generation ability,the form of rules,the application condition of rules,small universality and simulation software.The main contents of this dissertation are as follows.In this work,we focus on a small universal spiking neural P system with communication on request(SNQ P systems,for short).As a result,we construct a Turing universal SNQ P system with only 14 neurons,which answers an open problem whether the number of neurons for constructing a Turing universal SNQ P system can be further improved.We introduce evolution rules into cell-like spiking neural P systems(abbreviated as cSN P systems).We prove that cSN P systems with evolution rules are computationally universal.We also investigate the influence of the target indications on the computation power of cSN P systems with evolution rules.The results show that removing some target indications has no influence on computation power but a corresponding increase in the number of membranes.Besides,the results give a solution to the open problem that seeks alternative methods for the replication of spikes in a cSN P system.We implement the design and development of spiking neural P system with communication on request simulation software.The simulation program developed here reads the structured text file which defines the membrane system and intuitively generates the calculation process transition diagram of SNQ P system.In this way,we can accurately and quickly verify all the calculations that may occur in a specific step of SNQ P system.The simulation results of SNQ P system show that the simulation program can accurately simulate and verify the calculation process and results.