• DocumentCode
    3044666
  • Title

    Analogous memory utilization-a necessary characteristic for large, adaptive neural net

  • Author

    Fortune, James A.

  • Author_Institution
    Oakland Univ., Rochester, MI, USA
  • fYear
    1989
  • fDate
    14-17 Nov 1989
  • Firstpage
    1268
  • Abstract
    When confronted with new knowledge structured in a familiar way humans often rely on analogy to make a one-to-one correspondence to the familiar structure. The author notes that efficient adaptive neural nets also have that characteristic. In fact, the absence of analogous memory utilization from a system will be obvious because the resulting uncontrolled redundancy will quickly fill new memory with an exponential explosion of redundant information. The resulting decrease in performance is rapid and dramatic. A discussion is presented of why proper use of available memory will produce analogous memory utilization automatically
  • Keywords
    knowledge engineering; memory architecture; neural nets; adaptive neural net; analogous memory utilization; redundancy; Artificial intelligence; Biological neural networks; Entropy; Explosions; Hardware; Humans; Natural languages; Neural networks; Robot motion; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1989. Conference Proceedings., IEEE International Conference on
  • Conference_Location
    Cambridge, MA
  • Type

    conf

  • DOI
    10.1109/ICSMC.1989.71507
  • Filename
    71507