A novel encoding strategy for associative memory

  • Han-Bing Ji
  • Kwong-Sak Leung
  • Yee Leung
Oral Presentations: Theory Theory I: Associative Memory
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)


A novel encoding strategy for neural associative memory is presented in this paper. Unlike the conventional pointwise outer-product rule used in the Hopfield-type associative memories, the proposed encoding method computes the connection weight between two neurons by summing up not only the products of the corresponding two bits of all fundamental memories but also the products of their neighboring bits. Theoretical results concerning stability and attractivity are given. It is found both theoretically and experimentally that the proposed encoding scheme is an ideal approach for making the fundamental memories fixed points and maximizing the storage capacity which can be many times of the current limits.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    J. J. Hopfield, “Neural networks and physical systems with emergent collective computational abilities,” Proc. Natl. Acad. Sci., USA, vol.79, pp.2554–2558, April 1982.Google Scholar
  2. 2.
    R. J. McEliece, E. C. Posner, E. R. Rodemich and S. S. Venkatesh, “The capacity of the Hopfield associative memory,” IEEE Trans. on Information Theory, vol.IT-33, no.4, pp.461–482, July 1987.Google Scholar
  3. 3.
    Y.-F. Wang, J. B. Cruz and J. H. Mulligan, “Guaranteed recall of all training pairs for bidirectional associative memory,” IEEE Trans. on Neural Networks, vol.2, no.6, pp.559–567, Nov. 1991.Google Scholar
  4. 4.
    K.-S. Leung, H.-B. Ji, and Y. Leung, “Adaptive weighted outer-product learning associative memory,” to be published in IEEE Trans. on Systems, Man, and Cybernetics.Google Scholar
  5. 5.
    T.-D. Chiueh and R. M. Goodman, “Recurrent correlation associative memories,” IEEE Trans. on Neural Networks, vol.2, no.2, pp.275–284, March 1991.Google Scholar
  6. 6.
    M. Morita, “Associative memory with nonmonotone dynamics,” Neural Networks, vol.6, pp.115–126, 1993.Google Scholar
  7. 7.
    H. Nishimori and I. Opris, “Retrieval process of an associative memory with a general input-output function,” Neural Networks, vol.6, pp.1061–1067, 1993.Google Scholar
  8. 8.
    B.-L. Zhang, B.-Z. Xu and C.-P. Kwong, “Performances analysis of the bidirectional associative memory and an improved model from the matched-filtering viewpoint,” IEEE Trans. on Neural Networks, vol.4, no.5, pp.864–872, Sept. 1993.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Han-Bing Ji
    • 1
  • Kwong-Sak Leung
    • 1
  • Yee Leung
    • 1
  1. 1.Dept. of Computer Science and EngineeringThe Chinese University of Hong KongShatin, N.T.Hong Kong

Personalised recommendations