Skip to main content

Spiking Neural P Systems Used as Acceptors and Transducers

(Extended Abstract of an Invited Talk)

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4783))

Abstract

The study of spiking neural P systems is a branch of membrane computing (comprehensive information about this area of natural computing can be found in [24], [9], or at the web page [31]) initiated in [18]. The goal is to build a model of the way the neurons cooperate in (large) neural nets, communicating by means of spikes, electrical impulses of identical shapes. “Computing by spiking” is a vivid research area in neural computing, which promises to lead to a neural computing “of the third generation” - see [12], [22], etc.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alhazov, A., Freund, R., Oswald, M., Slavkovik, M.: Extended variants of spiking neural P systems generating strings and vectors of non-negative integers. In [14], pp. 123–134

    Google Scholar 

  2. Cavaliere, M., Egecioglu, E., Ibarra, O.H., Ionescu, M., Păun, Gh., Woodworth, S.: Asynchronous spiking neural P systems; decidability and undecidability, 2006 (submitted)

    Google Scholar 

  3. Chen, H., Freund, R., Ionescu, M., Păun, Gh., Pérez-Jiménez, M.J.: On string languages generated by spiking neural P systems. In [13], vol. I, pp. 169–194

    Google Scholar 

  4. Chen, H., Ionescu, M., Ishdorj, T.-O.: On the efficiency of spiking neural P systems. In [13], vol. I, pp. 195–206. In: Proc. 8th Intern. Conf. on Electronics, Information, and Communication, Ulanbator, Mongolia, pp. 49–52 (June 2006)

    Google Scholar 

  5. Chen, H., Ionescu, M., Păun, A., Păun, Gh., Popa, B.: On trace languages generated by spiking neural P systems. In [13], Proc. DCFS 2006, Las Cruces, NM, vol. I, pp. 207–224 (June 2006)

    Google Scholar 

  6. Chen, H., Ishdorj, T.-O., Păun, Gh.: Computing along the axon. In [13], vol. I, pp. 225–240

    Google Scholar 

  7. Chen, H., Ishdorj, T.-O., Păun, Gh., Pérez-Jiménez, M.J.: Spiking neural P systems with extended rules. In [13], vol. I, pp. 241–265

    Google Scholar 

  8. Chen, H., Ishdorj, T.-O., Păun, Gh., Pérez-Jiménez, M.J.: Handling languages with spiking neural P systems with extended rules. Romanian J. Information Sci. and Technology 9(3), 151–162 (2006)

    Google Scholar 

  9. Ciobanu, G., Păun, Gh., Pérez-Jiménez, M.J. (eds.): Applications of Membrane Computing. Springer, Berlin (2006)

    Google Scholar 

  10. Freund, R., Oswald, M.: Spiking neural P systems with inhibitory axons. In: Proc. AROB Conf., Japan (2007)

    Google Scholar 

  11. García-Arnau, M., Peréz, D., Rodriguez-Patón, A., Sosík, P.: Spiking neural P systems. Stronger normal forms (submitted, 2007)

    Google Scholar 

  12. Gerstner, W., Kistler, W.: Spiking Neuron Models. Single Neurons, Populations, Plasticity. Cambridge Univ. Press, Cambridge (2002)

    MATH  Google Scholar 

  13. Gutiérrez-Naranjo, M.A., et al. (eds.): Proceedings of Fourth Brainstorming Week on Membrane Computing, Fenix Editora, Sevilla (February 2006)

    Google Scholar 

  14. Hoogeboom, H.J., Păun, Gh., Rozenberg, G., Salomaa, A. (eds.): WMC 2006. LNCS, vol. 4361. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  15. Ibarra, O.H., Păun, A., Păun, Gh., Rodríguez-Patón, A., Sosík, P., Woodworth, S.: Normal forms for spiking neural P systems. In [13], vol. II, 105–136. Theoretical Computer Sci. 372(2-3), 196–217 (2007)

    Article  MATH  Google Scholar 

  16. Ibarra, O.H., Woodworth, S.: Characterizations of some restricted spiking neural P systems. In [14], pp. 424–442

    Google Scholar 

  17. Ibarra, O.H., Woodworth, S., Yu, F., Păun, A.: On spiking neural P systems and partially blind counter machines. In: UC 2006. Proceedings of Fifth Unconventional Computation Conference, York, UK (September 2006)

    Google Scholar 

  18. Ionescu, M., Păun, Gh., Yokomori, T.: Spiking neural P systems. Fundamenta Informaticae 71(2-3), 279–308 (2006)

    MATH  MathSciNet  Google Scholar 

  19. Ionescu, M., Păun, Gh., Yokomori, T.: Spiking neural P systems with exhaustive use of rules. Intern. J. Unconventional Computing (to appear)

    Google Scholar 

  20. Korec, I.: Small universal register machines. Theoretical Computer Science 168, 267–301 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  21. Leporati, A., Zandron, C., Ferretti, C., Mauri, G.: On the computational power of spiking neural P systems (submitted, 2007)

    Google Scholar 

  22. Maass, W., Bishop, C. (eds.): Pulsed Neural Networks. MIT Press, Cambridge (1999)

    Google Scholar 

  23. Păun, A., Păun, Gh.: Small universal spiking neural P systems. In [13], BioSystems II, 213–234 (in press)

    Google Scholar 

  24. Păun, Gh.: Membrane Computing. An Introduction. Springer, Berlin (2002)

    Google Scholar 

  25. Păun, Gh.: Twenty six research topics about spiking neural P systems.available at [31], (2006)

    Google Scholar 

  26. Păun, Gh.: Spiking neural P systems. Power and efficiency. In: Proc. IWINAC, Mar Menor, Spain (2007)

    Google Scholar 

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

    Article  Google Scholar 

  28. Păun, Gh., Pérez-Jiménez, M.J., Rozenberg, G.: Infinite spike trains in spiking neural P systems, 2005 (submitted)

    Google Scholar 

  29. Păun, Gh., Pérez-Jiménez, M.J., Rozenberg, G.: Computing morphisms by spiking neural P systems. Intern. J. Found. Computer Sci. (to appear)

    Google Scholar 

  30. Ramírez-Martínez, D., Gutiérrez-Naranjo, M.A.: A software tool for dealing with spiking neural P systems (submitted, 2007)

    Google Scholar 

  31. The P Systems Web Page, http://psystems.disco.unimib.it

Download references

Author information

Authors and Affiliations

Authors

Editor information

Jan Holub Jan Žďárek

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Păun, G. (2007). Spiking Neural P Systems Used as Acceptors and Transducers. In: Holub, J., Žďárek, J. (eds) Implementation and Application of Automata. CIAA 2007. Lecture Notes in Computer Science, vol 4783. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76336-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-76336-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76335-2

  • Online ISBN: 978-3-540-76336-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics