Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5517))

Included in the following conference series:

  • 2071 Accesses

Abstract

We present a new model of unsupervised competitive neural network, based on spicules. This model is capable of detecting topological information of an input space, determining its orientation and, in most case, its skeleton.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Willshaw, D.J., von der Malsburg, C.: How patterned neural connections can be set up by self-organization. Proc. of the Royal Society of London B 194, 431–445 (1976)

    Article  Google Scholar 

  2. Grossberg, S.: Adaptative pattern classification and universal recording: parallel development and coding of neural detectors. Biol. Cyber. 23, 121–134 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43, 59–69 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  4. Kohonen, T.: The neural phonetic typewriter. IEEE Computer 21, 11–22 (1988)

    Article  Google Scholar 

  5. Favata, F., Walker, R.: A study of the application of Kohonen-type neural networks to the traveling salesman problem. Biological Cybernetics 64, 463–468 (1991)

    Article  MATH  Google Scholar 

  6. López-Rubio, E., Muñoz-Pérez, J., Gómez-Ruiz, J.A.: Invariant pattern identification by self-organizing networks. Pattern Recognition Letters 22, 983–990 (2001)

    Article  MATH  Google Scholar 

  7. Gómez-Ruiz, J.A., López Rubio, E., Muñoz Pérez, J.: Expansive competitive learning for colour imagen compression. In: Proceedings of the II international symposium on neural computation, Berlin, Germany, pp. 522–527 (2000)

    Google Scholar 

  8. Fiesler, E., Beale, R.: Handbook of Neural Computation. Oxford University Press, Oxford (1997)

    Book  MATH  Google Scholar 

  9. Fritzke, B.: Growing cell structures: a self-organizing network for unsupervised and supervised learning. Neural Networks 7(9), 1441–1460 (1994)

    Article  Google Scholar 

  10. Martinetz, T.M.: Competitive hebbian learning rule forms perfectly topology preserving maps. In: Proceedings of the International Conference on Artificial Neural Networks, Amsterdam, Holland, pp. 427–434 (1993)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gómez-Ruiz, J.A., Muñoz-Perez, J., García-Bernal, M.A. (2009). Spicules for Unsupervised Learning. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02478-8_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02477-1

  • Online ISBN: 978-3-642-02478-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics