title: Time-free spiking neural P systems.
abstract: Different biological processes take different times to be completed, which can also be influenced by many environmental factors. In this work, a realistic definition of nonsynchronized spiking neural P systems (SN P systems, for short) is considered: during the work of an SN P system, the execution times of spiking rules cannot be known exactly (i.e., they are arbitrary). In order to establish robust systems against the environmental factors, a special class of SN P systems, called time-free SN P systems, is introduced, which always produce the same computation result independent of the execution times of the rules. The universality of time-free SN P systems is investigated. It is proved that these P systems with extended rules (several spikes can be produced by a rule) are equivalent to register machines. However, if the number of spikes present in the system is bounded, then the power of time-free SN P systems falls, and in this case, a characterization of semilinear sets of natural numbers is obtained.
authors.affiliation: Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China. lqpan@mail.hust.edu.cn
authors.forename: Linqiang
authors.initials: L
authors.lastname: Pan
authors.forename: Xiangxiang
authors.initials: X
authors.lastname: Zeng
authors.forename: Xingyi
authors.initials: X
authors.lastname: Zhang
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D001185:Artificial Intelligence; D003071:Cognition / Q000502:physiology; D003198:Computer Simulation / Q000592:standards*; D006801:Humans; D055641:Mathematical Concepts; D008962:Models, Theoretical; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D009435:Synaptic Transmission / Q000502:physiology; D013997:Time Factors