Title: Spiking neural P systems with anti-spikes and without annihilating priority working in a 'flip-flop' way

Authors: Gangjun Tan; Tao Song; Zhihua Chen; Xiangxiang Zeng

Addresses: Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China ' Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China ' Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China ' Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China

Abstract: Spiking neural P systems with anti-spikes (ASN P systems, for short) are a variant of spiking neural P systems, which are inspired by inhibitory impulses/spikes in biological neural systems. In general ASN P systems, spikes and anti-spikes can annihilate with each other when they meet in a neuron. The annihilation has priority to using spiking and forgetting rules, and takes no time to finish. In this work, we consider ASN P systems without annihilating priority with neurons working in a 'flip-flop' way, that is each neuron can only produce spikes by anti-spikes or produce anti-spikes from spikes. As results, such systems achieve the Turing completeness as number generator. This gives a positive answer to an open problem left in IJCCC (2009, Vol. IV, No. 3, pp.273-282).

Keywords: membrane computing; Turing completeness; spiking neural P systems; anti-spikes; annihilating priority; neurons.

DOI: 10.1504/IJCSM.2013.055208

International Journal of Computing Science and Mathematics, 2013 Vol.4 No.2, pp.152 - 162

Received: 23 Mar 2013
Accepted: 25 Mar 2013
Published online: 10 May 2014 *

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