Spiking neural P systems with anti-spikes and without annihilating priority working in a 'flip-flop' way Online publication date: Sat, 10-May-2014
by Gangjun Tan; Tao Song; Zhihua Chen; Xiangxiang Zeng
International Journal of Computing Science and Mathematics (IJCSM), Vol. 4, No. 2, 2013
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).
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com