Information and pattern capacities in neural associative memories with feedback for sparse memory patterns

  • Günther Palm
  • Friedrich T. Sommer
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


How to judge the performance of associative memories in applications? Using information theory, we examine the static structure of memory states and spurious states of a recurrent associative memory after learning. In this framework we consider the critical pattern capacity often used in the literature and introduce the information capacity as a more relevant performance measure for pattern completion. For two types of local learning rule, the Hebb and the clipped Hebb rule our method yields new asymptotic estimates for the information capacity.


Error Probability Quality Criterion Channel Capacity Associative Memory Memory State 
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Copyright information

© Springer-Verlag London Limited 1992

Authors and Affiliations

  • Günther Palm
    • 1
  • Friedrich T. Sommer
    • 1
  1. 1.C. u. O. Vogt Institut für HirnforschungUniversity of DüsseldorfDüsseldorf 1Germany

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