On string languages generated by sequential spiking neural P systems based on the number of spikes
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Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, we consider SN P systems with the following restriction: at each step the active neuron with the maximum (or minimum) number of spikes among the neurons that can spike will fire [if there is a tie for the maximum (or minimum) number of spikes stored in the active neurons, only one of the neurons containing the maximum (or minimum) is chosen non-deterministically]. We investigate the computational power of such sequential SN P systems that are used as language generators. We prove that recursively enumerable languages can be characterized as projections of inverse-morphic images of languages generated by such sequential SN P systems. The relationships of the languages generated by these sequential SN P systems with finite and regular languages are also investigated.
KeywordsMembrane computing Spiking neural P system Sequentiality Language generator
This is an expanded version of a paper presented at Unconventional Computation & Natural Computation 2014, University of Western Ontario, London, Ontario, Canada, 14–18 July 2014. This work was supported by National Natural Science Foundation of China (61033003, 91130034 and 61320106005), Ph.D. Programs Foundation of Ministry of Education of China (20120142130008), Anhui Provincial Natural Science Foundation (1408085MF131), Natural Science Research Project for Higher Education Institutions of Anhui Province(KJ2014A140).
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