Skip to main content
SpringerLink
Log in

Information efficiency of the associative net at arbitrary coding rates

  • Oral Presentations: Theory Theory I: Associative Memory
  • Conference paper
  • First Online:
Book cover Artificial Neural Networks — ICANN 96 (ICANN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1112))

Included in the following conference series:

Abstract

The associative net is a neural network model of associative memory that is unusual in having binary-valued connections between units. This net can work with high information efficiency, but only if the patterns to be stored are extremely sparse. In this paper we report how the efficiency of the net can be improved for more dense coding rates by using a partially-connected net. The information efficiency can be maintained at a high level over a 2–3 order of magnitude variation in the degree of pattern sparseness.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Amaral, D., Ishizuka, N., & Claiborne, B. (1990). Neurons, numbers and the hippocampal network. In Storm-Mathisen, J., Zimmer, J., & Ottersen, O. (Eds.), Progress in Brain Research, Vol.83, pp. 1–11. Elsevier Science Publishers B.V.

    Google Scholar 

  • Buckingham, J., & Willshaw, D. (1992). Performance characteristics of the associative net. Network, 3, 407–414.

    Google Scholar 

  • Buckingham, J., & Willshaw, D. (1993). On setting unit thresholds in an incompletely connected associative net. Network, 4, 441–459.

    Google Scholar 

  • Gardner, E. (1987). Maximum storage capacity in neural networks. Europhysics Letters, 4, 481.

    Google Scholar 

  • Graham, B., & Willshaw, D. (1995). Improving recall from an associative memory. Biol. Cybern., 72, 337–346.

    Google Scholar 

  • Graham, B., & Willshaw, D. (1994). Capacity and information efficiency of a brain-like associative net. In Tesauro, G., Touretzky, D., & Leen, T. (Eds.), Neural Information Processing Systems 7, pp. 513–520. MIT Press.

    Google Scholar 

  • Nadal, J.-P., & Toulouse, G. (1990). Information storage in sparsely coded memory nets. Network, 1, 61–74.

    Google Scholar 

  • Willshaw, D. (1971). Models of distributed associative memory. Ph.D. thesis, University of Edinburgh.

    Google Scholar 

  • Willshaw, D., Buneman, O., & Longuet-Higgins, H. (1969). Non-holographic associative memory. Nature, 222, 960–962.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Cognitive Science, University of Edinburgh, 2 Buccleuch Place, EH8 9LW, Edinburgh, Scotland, UK

    Bruce Graham & David Willshaw

Authors
  1. Bruce Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David Willshaw
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Christoph von der Malsburg Werner von Seelen Jan C. Vorbrüggen Bernhard Sendhoff

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Graham, B., Willshaw, D. (1996). Information efficiency of the associative net at arbitrary coding rates. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_10

Download citation

  • DOI: https://doi.org/10.1007/3-540-61510-5_10

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61510-1

  • Online ISBN: 978-3-540-68684-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation