Skip to main content
SpringerLink
Log in

A uniform solution to integer factorization using time-free spiking neural P system

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Spiking neural P system is a class of bio-inspired computing model; a feature of traditional SN P system is that the precise execution time of each rule plays a crucial role. However, the execution that each rule has a precise execution time does not coincide with the biological fact, since the execution time of biochemical reactions can vary because of external uncontrollable conditions. SN P systems that work independently from the values associated with the execution times of the rules were investigated in Pan et al. (Neural Comput 23(5):1320–1342, 2011). In this work, we give a time-free solution to integer factorization problem by SN P systems, which means the execution times of the rules specified by different time mappings have no influence on the correctness of the solution. Besides, we prove that the systems are constructed in a uniform manner.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Cavaliere M (2012) Time-free solution to hard computational problems. In: 10th brainstorming week on membrane computing, pp 204–210, Sevilla

  2. Cavaliere M, Sburlan D (2005) Time-independent P systems. In: Mauri G, Păun G, Jesús Pérez-Jímenez M, Rozenberg G, Salomaa A (eds) Membrane computing, WMC 2004. LNCS, vol 3365. Springer, Heidelberg, pp 239–258

  3. Cavaliere M, Ibarra OH, Păun G, Egecioglu O, Ionescu M, Woodworth S (2009) Asynchronous spiking neural P systems. Theor Comput Sci 410(24):2352–2364

    Article  MATH  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

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

    MATH  Google Scholar 

  6. Ishdorj TO, 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  MATH  MathSciNet  Google Scholar 

  7. Leporati A, Zandron C, Ferretti C, Mauri G (2007) Solving numerical NP-complete problem with spiking neural P systems. In: Eleftherakis G, Kefalas P, Păun GH, Rozenberg G, Salomaa A (eds) Membrane computing, International Workshop, WMC8, Selected and Invited Papers, Lecture Notes in Computer Science, vol 4860. Springer, pp 336–352

  8. 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  MATH  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  10. 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  MATH  MathSciNet  Google Scholar 

  11. Pan L, Zeng X, Zhang X (2011) Time-free spiking neural P systems. Neural Comput 23(5):1320–1342

    Article  MATH  MathSciNet  Google Scholar 

  12. Pan L, Wang J, Hoogeboom HJ (2012) Spiking neural P systems with astrocytes. Neural Comput 24(3):805–825

    Article  MATH  MathSciNet  Google Scholar 

  13. Pan L, Zeng X, Zhang X, Jiang Y (2012) Spiking neural P systems with weighted synapses. Neural Process Lett 35(1):13–27

    Article  Google Scholar 

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

    Article  Google Scholar 

  15. Păun G (2000) Computing with membranes. J Comput Syst Sci 61(1):108–143

    Article  MATH  MathSciNet  Google Scholar 

  16. Păun G, Pérez-Jiménez MJ, Rozenberg G (2006) Spike trains in spiking neural P systems. Int J Found Comput Sci 17(04):975–1002

    Article  MATH  Google Scholar 

  17. Păun G (2002) Membrane computing: an introduction. Springer, Berlin

    Book  Google Scholar 

  18. Păun G, Rozenberg G, Salomaa A (2010) The Oxford handbook of membrane computing. Oxford University Press Inc, Oxford

    Book  MATH  Google Scholar 

  19. Song T, Pan L, Wang J, Venkat I, Subramanian K, Abdullah R (2012) Normal forms of spiking neural P systems with anti-spikes. IEEE Trans Nanobioscience 11:352–359

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  21. Song T, Wang X, Zheng H (2013) Time-free solution to hamilton path problems using P systems with d-division. J Appl Math. Article ID 975798, 7 pages, 2013. doi:10.1155/2013/975798

  22. Song T, Luo L, He J, Chen Z, Zhang K (2014) Solving subset sum problems by time-free spiking neural P systems. Appl Math Inf Sci 8(1):327–332

    Article  Google Scholar 

  23. Song T, Macías-Ramos LF, Pan L, Pérez-Jiménez MJ (2014) Time-free solution to SAT problem using P systems with active membranes. Theor Comput Sci 529:61–68

    Article  MATH  Google Scholar 

  24. Wang J, Shi P, Peng H, Perez-Jimenez MJ, Wang T (2013) Weighted fuzzy spiking neural P systems. IEEE Trans Fuzzy Syst 21(2):209–220

    Article  Google Scholar 

  25. Zeng X, Pan L, Pérez-Jiménez MJ (2014) Small universal simple spiking neural P systems with weights. Sci China Inf Sci 57(9):1–11

    Article  MATH  Google Scholar 

  26. Zeng X, Xu L, Liu X, Pan L (2014) On languages generated by spiking neural P systems with weights. Inf Sci 278:423–433

    Article  MathSciNet  Google Scholar 

  27. Zeng X, Zhang X, Song T, Pan L (2014) Spiking neural P systems with thresholds. Neural Comput pp 1–22

  28. Zhang G, Rong H, Neri F, Pérez-Jiménez MJ (2014) An optimization spiking neural P system for approximately solving combinatorial optimization problems. Int J Neural Syst 24(05):1–15

    Article  Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgments

The work was supported by National Natural Science Foundation of China (Grant Nos. 61472333, 51405408, 61370010 and 71103154), China Scholarship Council (201308350065), Natural Science Foundation of Fujian Province of China (No. 2011J01334, 2014J01253), Base Research Project of Shenzhen Bureau of Science, Technology, and Information (JCYJ20120618155655087, JC201006030858A).

Author information

Authors and Affiliations

  1. Department of Computer Science, School of Information Science and Engineering, Xiamen University, Xiamen, China

    Xiangrong Liu, Ziming Li, Juan Suo & Xiaoping Min

  2. Department of Electric and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, USA

    Xiangrong Liu

  3. Department of Mechanical and Electrical Engineering, Institute of Physical and Mechanical and Electrical Engineering, Xiamen University, Xiamen, China

    Juan Liu

Authors
  1. Xiangrong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ziming Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan Suo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xiaoping Min
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoping Min.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, X., Li, Z., Suo, J. et al. A uniform solution to integer factorization using time-free spiking neural P system. Neural Comput & Applic 26, 1241–1247 (2015). https://doi.org/10.1007/s00521-014-1799-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-014-1799-2

Keywords

Search

Navigation