• DocumentCode
    746438
  • Title

    An excellent weight-updating-linearity EEPROM synapse memory cell for self-learning Neuron-MOS neural networks

  • Author

    Kosaka, Hideo ; Shibata, Tadashi ; Ishii, Hiroshi ; Ohmi, Tadahiro

  • Author_Institution
    Dept. of Electron. Eng., Tohoku Univ., Sendai, Japan
  • Volume
    42
  • Issue
    1
  • fYear
    1995
  • fDate
    1/1/1995 12:00:00 AM
  • Firstpage
    135
  • Lastpage
    143
  • Abstract
    A new synapse memory cell employing floating-gate EEPROM technology has been developed which is characterized by an excellent weight-updating linearity under the constant-pulse programming. Such a feature has been realized for the first time by employing a simple self-feedback regime in each cell circuitry. The potential of the floating gate is set to the tunneling electrode by the source follower action of the built-in cell circuitry, thus assuring a constant electric field strength in the tunnel oxide at each programming cycle independent of the stored charge in the floating gate. The synapse cell is composed of only seven transistors and inherits all the advanced features of the original six-transistor cell, such as the standby-power free and dual polarity characteristics. In addition, by optimizing the intra-cell coupling capacitance ratios, the acceleration effect in updating the weight has also been accomplished. All these features make the new synapse cell fully compatible with the hardware learning architecture of the Neuron-MOS neural network. The new synapse cell concept has been verified by experiments using test circuits fabricated by a double-polysilicon CMOS process
  • Keywords
    CMOS memory circuits; EPROM; PLD programming; neural chips; programmable logic devices; recurrent neural nets; unsupervised learning; EEPROM synapse memory cell; constant electric field strength; constant-pulse programming; double-polysilicon CMOS process; dual polarity characteristics; floating-gate EEPROM technology; intra-cell coupling capacitance ratios; programming cycle; self-feedback regime; self-learning neuron-MOS neural networks; source follower action; standby-power free characteristics; tunneling electrode; weight-updating linearity; Capacitance; Circuit testing; Coupling circuits; EPROM; Electrodes; Linear programming; Linearity; Nonvolatile memory; Transistors; Tunneling;
  • fLanguage
    English
  • Journal_Title
    Electron Devices, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9383
  • Type

    jour

  • DOI
    10.1109/16.370025
  • Filename
    370025