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On string languages generated by sequential spiking neural P systems based on the number of spikes

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Abstract

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, we consider SN P systems with the following restriction: at each step the active neuron with the maximum (or minimum) number of spikes among the neurons that can spike will fire [if there is a tie for the maximum (or minimum) number of spikes stored in the active neurons, only one of the neurons containing the maximum (or minimum) is chosen non-deterministically]. We investigate the computational power of such sequential SN P systems that are used as language generators. We prove that recursively enumerable languages can be characterized as projections of inverse-morphic images of languages generated by such sequential SN P systems. The relationships of the languages generated by these sequential SN P systems with finite and regular languages are also investigated.

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References

  • Chen H, Freund R, Ionescu M, Păun Gh, Pérez-Jiménez MJ (2007) On string languages generated by spikng neural P systems. Fund Inform 75:141–162

    MathSciNet  MATH  Google Scholar 

  • Chen H, Ionescu M, Ishdorj T-O, Păun A, Păun Gh, Pérez-Jiménez MJ (2008) Spiking neural P systems with extended rules: universality and languages. Nat Comput 7(2):147–166

    Article  MathSciNet  MATH  Google Scholar 

  • Ibarra OH, Păun A, Rodríguez-Patón A (2009) Sequential SNP systems based on min/max spike number. Theor Comput Sci 410(30–32):2982–2991

    Article  MATH  Google Scholar 

  • Ionescu M, Păun G, Yokomori T (2006) Spiking neural P systems. Fund Inform 71(2–3):279–308

    MathSciNet  MATH  Google Scholar 

  • Ishdorj T-O, Leporati A, Pan L, Zeng X, Zhang X (2010) Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources. Theor Comput Sci 411(25):2345–2358

    Article  MathSciNet  MATH  Google Scholar 

  • Leporati A, Mauri G, Zandron C, Păun G, Pérez-Jiménez MJ (2009) Uniform solutions to sat and subset sum by spiking neural P systems. Nat Comput 8(4):681–702

    Article  MathSciNet  MATH  Google Scholar 

  • Minsky M (1967) Computation—finite and infinite machines. Prentice Hall, Englewood Cliffs, New Jersey

    MATH  Google Scholar 

  • Pan L, Păun G, Pérez-Jiménez MJ (2011) Spiking neural P systems with neuron division and budding. Sci China Inform Sci 54(8):1596–1607

    Article  MATH  Google Scholar 

  • Pan L, Zeng X (2011) Small universal spiking neural P systems working in exhaustive mode. IEEE Trans Nanobiosci 10(2):99–105

    Article  MathSciNet  Google Scholar 

  • Păun A, Păun Gh (2007) Small universal spiking neural P systems. BioSystems 90(1):48–60

    Article  Google Scholar 

  • Păun A, Sidoroff M (2012) Sequentiality induced by spike number in SNP systems: small universal machines. LNCS 7184:333–345

    Google Scholar 

  • Păun G, Pérez-Jiménez MJ, Rozenberg G (2006) Spike trains in spiking neural P systems. Int J Found Comput Sci 17(4):975–1002

    Article  MATH  Google Scholar 

  • Păun G, Rozenberg G, Salomaa A (eds) (2010) Handbook of membrane computing. Oxford University Press, Oxford

  • Rozenberg G, Salomaa A (eds) (1997) Handbook of formal languages, vol 3. Springer, Berlin

  • Song T, Pan L, Păun G (2013) Asynchronous spiking neural P systems with local synchronization. Inform Sci 219:197–207

    Article  MathSciNet  MATH  Google Scholar 

  • Wang J, Hoogeboom HJ, Pan L, Păun G, Pérez-Jiménez MJ (2010) Spiking neural P systems with weights. Neural Comput 22(10):2615–2646

    Article  MathSciNet  MATH  Google Scholar 

  • Zeng X, Zhang X, Pan L (2009) Homogeneous spiking neural P systems. Fund Inform 97:1–20

    MathSciNet  Google Scholar 

  • Zhang X, Zeng X, Pan L (2009) On languages generated by asynchronous spiking neural P systems. Theor Comput Sci 410(26):2478–2488

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang X, Zeng X, Pan L (2008a) On string languages generated by spiking neural P systems with exhaustive use of rules. Nat Comput 7(4):535–549

    Article  MathSciNet  MATH  Google Scholar 

  • Zhang X, Zeng X, Pan L (2008b) Smaller universal spiking neural P systems. Fund Inform 87(1):117–136

    MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

This is an expanded version of a paper presented at Unconventional Computation & Natural Computation 2014, University of Western Ontario, London, Ontario, Canada, 14–18 July 2014. This work was supported by National Natural Science Foundation of China (61033003, 91130034 and 61320106005), Ph.D. Programs Foundation of Ministry of Education of China (20120142130008), Anhui Provincial Natural Science Foundation (1408085MF131), Natural Science Research Project for Higher Education Institutions of Anhui Province(KJ2014A140).

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Correspondence to Linqiang Pan.

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Jiang, K., Chen, W., Zhang, Y. et al. On string languages generated by sequential spiking neural P systems based on the number of spikes. Nat Comput 15, 87–96 (2016). https://doi.org/10.1007/s11047-015-9514-5

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