• DocumentCode
    288474
  • Title

    An analysis of practical capacity of exponential bidirectional associative memory

  • Author

    Wang, Chua-Chin ; Tsai, Chang-Rong

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    1994
  • fDate
    27 Jun-2 Jul 1994
  • Firstpage
    1074
  • Abstract
    The practical capacity of exponential bidirectional associative memory (eBAM) considering fault tolerance and fixed dynamic range of VLSI circuits is discussed. Several factors are taken into consideration in the implementation of an eBAM VLSI circuits. First, the fault tolerance requirement leads to the discovery of the attraction radius of the basin for each stored pattern pair. Second, the bit-error probability of the eBAM has to be optimally small when a huge amount of pattern pairs are encoded in the eBAM. Third, the fixed dynamic range of a transistor or a diode operating in the subthreshold region results in a limited length of each stored pattern. Hence, the signal-noise-ratio (SNR) analysis approach is adopted to find the attraction radius, and the practical capacity. A maximal bit-error probability (Pe) is estimated. A maximal length of patterns under a fixed dynamic range is derived
  • Keywords
    VLSI; content-addressable storage; fault tolerant computing; memory architecture; neural chips; neural nets; probability; VLSI circuits; attraction radius; bit-error probability; diode; eBAM; eBAM VLSI circuits; exponential bidirectional associative memory; fault tolerance; fault tolerance requirement; fixed dynamic range; maximal bit-error probability; pattern pairs; signal-noise-ratio analysis; stored pattern pair; subthreshold region; transistor; Associative memory; Circuits; Diodes; Dynamic range; Equations; Fault tolerance; Magnesium compounds; Neural networks; Signal analysis; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374332
  • Filename
    374332