Cell-Like Spiking Neural P Systems With Request Rules

被引:36
|
作者
Pan, Linqiang [1 ,2 ]
Wu, Tingfang [1 ]
Su, Yansen [3 ]
Vasilakos, Athanasios V. [4 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Automat, Educ Minist China, Key Lab Image Informat Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China
[2] Zhengzhou Univ Light Ind, Sch Elect & Informat Engn, Zhengzhou 450002, Henan, Peoples R China
[3] Anhui Univ, Sch Comp Sci & Technol, Minist Educ, Key Lab Intelligent Comp & Signal Proc, Hefei 230601, Anhui, Peoples R China
[4] Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, SE-93187 Lulea, Sweden
基金
中国国家自然科学基金;
关键词
Bio-inspired computing; membrane computing; spiking neural P system; computation power; universality; NETWORKS; UNIVERSALITY; ALGORITHM;
D O I
10.1109/TNB.2017.2722466
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Cell-like spiking neural (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. cSN P 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 paper, 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 more 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.
引用
收藏
页码:513 / 522
页数:10
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