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Sequential spiking neural P systems with structural plasticity based on max/min spike number

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Abstract

Spiking neural P systems (in short, SNP systems) are parallel, distributed, and nondeterministic computing devices inspired by biological spiking neurons. Recently, a class of SNP systems known as SNP systems with structural plasticity (in short, SNPSP systems) was introduced. SNPSP systems represent a class of SNP systems that have dynamism applied to the synapses, i.e. neurons can use plasticity rules to create or remove synapses. In this work, we impose the restriction of sequentiality on SNPSP systems, using four modes: max, min, max-pseudo-, and min-pseudo-sequentiality. We also impose a normal form for SNPSP systems as number acceptors and generators. Conditions for (non)universality are then provided. Specifically, acceptors are universal in all modes, while generators need a nondeterminism source in two modes, which in this work is provided by the plasticity rules.

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Notes

  1. See e.g. [13] and [14] and references therein.

  2. An overview in [29] and the SNP systems chapter in [28].

  3. Introduced in [1] and improved and extended in [2].

  4. A good introduction is [26] and the P systems webpage at http://ppage.psystems.eu/, with a handbook in [28].

References

  1. Cabarle FGC, Adorna H, Ibo N (2013) Spiking neural P systems with structural plasticity. In: Pre-proceedings of 2nd Asian conference on membrane computing, Chengdu, China, pp 13–26, 4–7 November 2013

  2. Cabarle FGC, Adorna HN, Pérez-Jiménez MJ, Song T (2015) Spiking neural P systems with structural plasticity (to appear). Neural Comput Appl. doi:10.1007/s00521-015-1857-4

    MATH  Google Scholar 

  3. Cabarle FGC, Adorna HN, Pérez-Jiménez MJ (2015) Asynchronous spiking neural P systems (to appear). In: 14th Unconventional computation and natural computation, 31 Aug–04 Sept, Auckland, New Zealand

  4. Cavaliere M, Egecioglu O, Woodworth S, Ionescu I, Păun G (2008) Asynchronous spiking neural P systems: decidability and undecidability. In: DNA 2008, LNCS vol 4848, pp 246–255

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

    Article  MathSciNet  MATH  Google Scholar 

  6. Ibarra OH, Woodworth S (2007) Spiking neural P systems: some characterizations. In: FCT 2007, LNCS vol 4639, pp 23–37

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

    Article  MathSciNet  MATH  Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  9. Ionescu M, Păun G, Yokomori T (2007) Spiking neural P systems with an exhaustive use of rules. J Unconv Comput 3(2):135–153

    Google Scholar 

  10. Jiang K, Song T, Pan L (2013) Universality of sequential spiking neural P systems based on minimum spike number. Theor Comput Sci 499:88–97

    Article  MathSciNet  MATH  Google Scholar 

  11. Jiang K, Song T, Chen W, Pan L (2013) Homogeneous spiking neural P systems working in sequential mode induced by maximum spike number. J Comput Math 90(4):831–844

    MathSciNet  MATH  Google Scholar 

  12. Leporati A, Zandron C, Ferretti C, Mauri G (2007) Solving numerical NP-complete problems with spiking neural P systems. In: Eleftherakis et al (eds) WMC8 2007, LNCS vol 4860, pp 336–352

  13. Maass W, Bishop C (eds) (1999) Pulsed neural networks. MIT Press, Cambridge

    MATH  Google Scholar 

  14. Maass W (2002) Computing with spikes. Speci Issue Found Inform Process TELEMATIK 8(1):32–36

    Google Scholar 

  15. Macías-Ramos F, Pérez-Hurtado I, García-Quismondo M, Valencia-Cabrera L, Pérez-Jiménez MJ, Riscos-Núñez A (2012) A P-Lingua based simulator for spiking neural P systems. In: Gheorghe M et al (eds) CMC12 LNCS vol 7184, pp 257–281

  16. Macías-Ramos F, Pérez-Jiménez MJ, Song T, Pan L (2015) Extending simulation of asynchronous spiking neural P systems in P-Lingua. Fundam Inform 136(3):253–267

    MathSciNet  MATH  Google Scholar 

  17. Minsky M (1967) Computation: finite and infinite machines. Prentice Hall, Englewood Cliffs

    MATH  Google Scholar 

  18. Pan L, Păun G (2009) Spiking neural P systems with anti-spikes. J Comput Commun Control IV(3):273–282

    Article  Google Scholar 

  19. Pan L, Păun G (2010) Spiking neural P systems: an improved normal form. Theor Comput Sci 411(6):906–918

    Article  MathSciNet  MATH  Google Scholar 

  20. Pan L, Wang J, Hoogeboom HJ (2010) Spiking neural P systems with weights. Neural Comput 22:2615–2646

    Article  MathSciNet  MATH  Google Scholar 

  21. 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 

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

    Article  MathSciNet  MATH  Google Scholar 

  23. Pan L, Wang J, Hoogeboom JH (2012) Spiking neural P systems with astrocytes. Neural Comput 24:805–825

    Article  MathSciNet  MATH  Google Scholar 

  24. Păun A, Păun G (2007) Small universal spiking neural P systems. Biosystems 90:48–60

    Article  MATH  Google Scholar 

  25. Păun G (1999) Computing with membranes. J Compu Syst Sci 61(1):108–143

    Article  MathSciNet  MATH  Google Scholar 

  26. Păun Gh (2002) Membrane computing: an introduction. Springer, Berlin

    Book  MATH  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  28. Păun G, Rozenberg G, Salomaa A (eds) (2009) The Oxford handbook of membrane computing. Oxford University Press, Oxford

    Google Scholar 

  29. Păun G, Pérez-Jiménez MJ (2009) Spiking neural P systems. Recent results, research topics. In: Condon A et al (eds) Algorithmic bioprocesses. Springer, Berlin

    Google Scholar 

  30. Song T, Pan L, Păun G (2013) Asynchronous spiking neural P systems with local synchronization. Inf Sci 219(10):197–207

    Article  MathSciNet  MATH  Google Scholar 

  31. Song T, Pan L, Jiang K, Song B, Chen W (2013) Normal forms for some classes of sequential spiking neural P Systems. IEEE Trans NanoBiosci 12(3):1536–1541

    Google Scholar 

  32. Zeng X, Pan L, Pérez-Jiménez MJ (2014) Small universal simple spiking neural P systems with weights. Sci China Inf Sci 57:1–11

    MathSciNet  Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  34. Zeng X, Luo B, Pan L (2014) On some classes of sequential spiking neural P systems. Neural Comput 26:974–997

    Article  MathSciNet  Google Scholar 

  35. Zhang X, Wang B, Pan L (2014) Spiking neural P systems with a generalized use of rules. Neural Comput 26(12):2925–2943

    Article  MathSciNet  Google Scholar 

  36. Zhang X, Pan L, Păun A (2015) On the Universality of Axon P systems. IEEE Trans Neural Netw Learn Syst. doi:10.1109/TNNLS.2015.2396940

    MathSciNet  Google Scholar 

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Acknowledgments

Cabarle is supported by a scholarship from the DOST-ERDT of the Philippines. Adorna is funded by a DOST-ERDT Grant and the Semirara Mining Corp. Professorial Chair of the College of Engineering, UP Diliman. M.J. Pérez-Jiménez acknowledges the support of the Project TIN2012-37434 of the “Ministerio de Economía y Competitividad” of Spain, co-financed by FEDER funds. The authors are thankful for the useful comments from three anonymous reviewers who helped improve this work.

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Correspondence to Francis George C. Cabarle.

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Cabarle, F.G.C., Adorna, H.N. & Pérez-Jiménez, M.J. Sequential spiking neural P systems with structural plasticity based on max/min spike number. Neural Comput & Applic 27, 1337–1347 (2016). https://doi.org/10.1007/s00521-015-1937-5

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  • DOI: https://doi.org/10.1007/s00521-015-1937-5

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