Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 626-630.doi: 10.11896/JsJkx.190500120

• Interdiscipline & Application • Previous Articles     Next Articles

Computing Ability of Spiking Neural P System Based on Rough Rules

LUO Yun-fang1, TANG Cheng-e1 and WEI Jun2   

  1. 1 College of Electromechanical and Information Engineering,Guangxi Vocational and Technical College,Nanning 530226,China
    2 Guangxi Zhuang Autonomous Region Admission Examination Institute,Nanning 530021,China
  • Published:2020-07-07
  • About author:LUO Yun-fang, born in 1981, master, associate professor.His main research direction include big data application technology, and software engineering.
    TANG Cheng-e, born in 1983, master, lecturer.Her main research interests include neural networks and automation of electric power systems.
  • Supported by:
    This work was supported by the 2018 Research ProJect of Guangxi Vocational & Technical College(181102) and 2018 Guangxi College Young and Middle-aged Teachers’ Basic Ability Improvement ProJect(2018KY0951,2018KY0956).

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Abstract: Spiking neural P system inspired neurons cooperation processing pulse process in biological systems and proposed new calculation model.In order to further reflect the randomness of biological system,this paper proposed a new neuronal activation system,rough rule based spiking neural P system,which uses the concept of upper and lower approximations to establish the activation conditions of neurons.Then,the computing completeness of the improved spiking neural P system was proved.Finally,the ability of the system to generate automatic language was studied to illustrate its computing ability.The result shows that the improved spiking neural P system has strong computing ability.

Key words: Automatic language, Computing ability, Rough rule, Spiking neural

CLC Number: 

  • TP183
[1] PUN G.Computing with membranes.Joural of Computer and System Sciences,2000,61(1):108-143.
[2] PUN G.Membrane Computing.Berlin:Springer-Verlag,2002.
[3] CIOBANU G,PUN G,PREZ-JIMENEZ M,et al.Applica-tions of Membrane Computings.Springer,2006:89-95.
[4] PUN G,ROZENBERG G,SALOMAA A.The Oxford Handbook of Membrane Computing.Oxford University Press,2010:345-353.
[5] IONESCU M,PUN G YOKOMORI T.Spiking neural P systems.Fundamenta Informaticae,2006,71(2/3):279-308.
[6] PAN l,PAUN G.New Normal Forms for Spiking Neural P Systems//BWMC.2009:127-138.
[7] IBARRA O,PUN A,PUN G,et al.Normal forms for spiking neural P systems.Theoretical Computer Science,2007,372(2/3):196-217.
[8] PUN A,PUN G.Small universal spiking neural P systems.Biosystems,2007,90(l):48-60.
[9] CHEN H,IONESCU M,PREZ-JIMNEZ M J,et al.On string languages generated by spiking neural P systems.Fundamenta Informaticae,2007,75(1/2/3/4):141-162.
[10] IBARRA O,WOODWORTH S.Characterizing regular languages by spiking neural P systems.Intenational Journal of Foundations of Computer science,2007,18(6):1247-1256.
[11] CHEN H,IONESCU M,PUN A,et al.On trace languages generated by spiking neural P systems//Proceedings of Eighth International Workshop on Descriptional Complexity of Formal Systems.2006:94-105.
[12] NEARY T.A small universal spiking neural P system.Intern.Workshop.Computing with Biomolecules//Viena.2008:65-74.
[13] LEPORATI A,ZANDRON C,FERRETTI C,et al.On the computational power of spiking neural P systems.International Journal of Unconventional Computing,2009,5(5):459-473.
[14] WANG J,ISHDORJ T O,PAN L.About Efficiency of spiking neural P systems//BWMC.2009:235-252.
[15] IONESCU M,SBURLAN D.Some applications of spiking neural P systems.Computing and Informatics,2008,27:515-528.
[16] GUTIRREZ-NARANJO M,LEPORATI A.First steps to wards a CPU made of spiking neural P systems.International Journal of Computers Comnunications & Control,2009,4(3):244-252.
[17] METTA V,KRITHIVASAN K,GARG D.Modeling spikingneural P systems using timed Pettri nets//proceedings of Nature Biologically Inspired Computing.2009:25-30.
[18] CETERCHI R,TOMESCU A.Implementing sorting networks with Spiking neural P systems.Fundamenta Informaticae,2008,87(l):35-48.
[19] REID D,BARRETT-BAXENDALE M.Spatiotemporal Proces-
[20] sing in a spiking neural P system//Proceedings of Second International Conference on Developments in Systems Enginee-ring.2010:394-399.
[21] WANG J,PENG H.Fuzzy knowledge representation based on an improving spiking neural P system//Proceedings of Sixth International Conference on Natural Computation.2010:3012-3015.
[22] WANG T,WANG J,PENG H,et al.Knowledge representation using fuzzy spiking neural p system//Proceedings of IEEE Fifth International Conference on Bio Inspired Computing:Theories and Applications.2010:586-590.
[23] PENG H,WANG J.Adaptive spiking neural P systems//Proceedings of Sixth International Conference on Natural Computation.2010:3008-3011.
[24] WU T F,ZHANG Z Q,PUN G,et al.Cell-like spiking neural P systems.Theoretical Computer Science,2016,623:180-189.
[25] WU T F,ZHANG Z Q,PAN L Q.On languages generated by cell-like spiking neural P systems.IEEE Transactions on Nanobioscience,2016,15(5):455-467.
[26] WU T F,PUN A,ZHANG Z Q,et al.Spiking neural P systems with polarizations.IEEE Transactions on Neural Networks and Learning Systems,2018,29(8):3349-3360.
[27] GUTIRREZ-NARANJO M,PREZ-JIMNEZ M.A Spiking Neural P system based model for Hebbian Learning//Proceedings of Ninth Works hop on Membrane Computing.2008,189-207.
[28] IONESCU M,TIRNAUEA C.Dreams and spiking neural P systems.Romanian Journal of Information Science andTechno-logy,2009,12(2):209-217.
[29] HOPCROFT J,MOTWANI R,ULLMAN J.Introduction toAutomata Theory,Languages and Computation.Reading,Mass.Addison-Wesley,1979(32):20-25.
[30] CHOMSKY N.Three models for the description of language .IRE Transactions on Information Theory,1956,2(3):113-124.
[31] CHOMSKY N.On certain formal Properties of grammars.Information and Control,1959,2(2):137-167.
[32] MINSKY M.Computation:Finite and Infinite Machines.New Jersey:Prentice-Hall,1967.
[33] PAWLAK Z.Rough Sets.Theoretical Aspects of Reasoning About Data.Kluwer,Dordrecht,1991.
[34] PAWLAK Z.A treatise on rough sets//Transactions onRough Sets.Berlin:Springer-Verlag,2005:1-17.
[35] WU T F,BLBE F D,PUN A,et al.Ferrante Neri:Simplified and yet Turing universal spiking neural P systems with communication on request.International Journal of Neural Systems,28(8):1850013.
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[3] KOU Guang-jie,MA Yun-yan,YUE Jun and ZOU Hai-lin. Research Advance and Prospect of Membrane Computing Applied in Image Processing [J]. Computer Science, 2014, 41(Z11): 139-143.
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