• DocumentCode
    1264268
  • Title

    Two coding strategies for bidirectional associative memory

  • Author

    Wang, Yeou-Fang ; Cruz, Jose B., Jr. ; Mulligan, James H., Jr.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA
  • Volume
    1
  • Issue
    1
  • fYear
    1990
  • fDate
    3/1/1990 12:00:00 AM
  • Firstpage
    81
  • Lastpage
    92
  • Abstract
    Enhancements of the encoding strategy of a discrete bidirectional associative memory (BAM) reported by B. Kosko (1987) are presented. There are two major concepts in this work: multiple training, which can be guaranteed to achieve recall of a single trained pair under suitable initial conditions of data, and dummy augmentation, which can be guaranteed to achieve recall of all trained pairs if attaching dummy data to the training pairs is allowable. In representative computer simulations, multiple training has been shown to lead to an improvement over the original Kosko strategy for recall of multiple pairs as well. A sufficient condition for a correlation matrix to make the energies of the training pairs be local minima is discussed. The use of multiple training and dummy augmentation concepts are illustrated, and theorems underlying the results are presented
  • Keywords
    content-addressable storage; encoding; neural nets; Kosko strategy; bidirectional associative memory; correlation matrix; dummy augmentation; encoding strategy; multiple training; neural nets; sufficient condition; Associative memory; Computer simulation; Encoding; Iterative decoding; Joining processes; Magnesium compounds; Manufacturing; Neural networks; Subcontracting; Sufficient conditions;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.80207
  • Filename
    80207