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 restriction: at each step the neuron with the maximum number of spikes among the neurons that can spike will fire (if there is a tie for the maximum number of spikes stored in the active neurons, only one of the neurons containing the maximum 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 that sequential SN P systems. The relationships of the languages generated by these sequential SN P systems with finite and regular languages are also investigated. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Jiang, K., Zhang, Y., & Pan, L. (2014). On string languages generated by sequential spiking neural P systems based on maximum spike number. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8553 LNCS, pp. 203–215). Springer Verlag. https://doi.org/10.1007/978-3-319-08123-6_17
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