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Cell-like spiking neural P systems with request rules
Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan.
Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan.
Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei.
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-1902-9877
2017 (engelsk)Inngår i: IEEE Transactions on Nanobioscience, ISSN 1536-1241, E-ISSN 1558-2639, Vol. 16, nr 6, s. 513-522Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Cell-like spiking neural P systems (in short, cSN P systems) are a class of distributed and parallel computation models inspired by both the way in which neurons process information and communicate to each other by means of spikes and the compartmentalized structures of living cells. cSNP systems have been proved to be Turing universal if more spikes can be produced by consuming some spikes or spikes can be replicated. In this work, in order to answer the open problem whether this functioning of producing more spikes and replicating spikes can be avoided by using some strategy without the loss of computation power, we introduce cSN P systems with request rules, which have classical spiking rules and forgetting rules, and also request rules in the skin membrane. The skin membrane can receive spikes from the environment by the application of request rules. cSN P systems with request rules are proved to be Turing universal. The results show that the decrease of computation power caused by removing the internal functioning of producing spikes and replicating spikes can be compensated by request rules, which suggests that the communication between a cell and the environment is an essential ingredient of systems in terms of computation power.

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Institute of Electrical and Electronics Engineers (IEEE), 2017. Vol. 16, nr 6, s. 513-522
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URN: urn:nbn:se:ltu:diva-65718DOI: 10.1109/TNB.2017.2722466ISI: 000411682900013OAI: oai:DiVA.org:ltu-65718DiVA, id: diva2:1142371
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Validerad;2017;Nivå 2;2017-10-04 (andbra)

Tilgjengelig fra: 2017-09-19 Laget: 2017-09-19 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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