Skip to main content

Extending Kohonen’s Self-Organizing Mapping Algorithm to Learn Ballistic Movements

  • Conference paper

Part of the book series: Springer Study Edition ((SSE,volume 41))

Abstract

Rapid limb movements are known to be initiated by a brief torque pulse at the joints and to proceed freely thereafter (ballistic movements). To initiate such movements with a desired starting velocity u requires knowledge of the relation between torque pulse and desired velocity of the limb. We show for a planar two-link arm model that this relationship can be learnt with the aid of a self-organizing mapping of the type proposed earlier by Kohonen. To this end we extend Kohonen’s algorithm by a suitable learning rule for the individual units and show that this approach results in a significant improvement in the convergency properties of the learning rule used.

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   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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. Brady M., Hollerbach J.M., Johnson T.L., Lozano-Perez T., Mason M.T. (eds): Robot Motion: Planning and Control, Cambridge Massachusets: MIT-Press 1984

    Google Scholar 

  2. Kohonen T.: Self-organized Formation of Topologically Correct Feature Maps. Biol. Cybern. 43, pp. 59–69 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kohonen T.: Analysis of a Simple Self-organizing Process. Biol. Cybern. 44, pp. 135–140 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  4. Kohonen T.: Self-Organization and Associative Memory, Heidelberg, Springer Series in Information Sciences 8 , 1984

    MATH  Google Scholar 

  5. Ritter H., Schulten K.: On the stationary state of Kohonen’s Self-Organizing Sensory Mapping. Biol.Cybern. 54, pp. 99–106 (1986)

    Article  MATH  Google Scholar 

  6. Ritter H., Schulten K.: Topology Conserving Mappings for Learning Motor Tasks. In J.S. Denker (Ed.), Neural Networks for Computing, AIP Conf. Proceedings 151, Snowbird/Utah 1986

    Google Scholar 

  7. Rumelhart D.E., McClelland J.L.: Parallel Distributed Processing (Vol.1), Cambridge Massachusets: MIT-Press 1984

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ritter, H., Schulten, K. (1989). Extending Kohonen’s Self-Organizing Mapping Algorithm to Learn Ballistic Movements. In: Eckmiller, R., v.d. Malsburg, C. (eds) Neural Computers. Springer Study Edition, vol 41. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83740-1_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-83740-1_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-50892-2

  • Online ISBN: 978-3-642-83740-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics