• DocumentCode
    2831020
  • Title

    VLSI implementation of a transconductance mode continuous BAM with on chip learning and dynamic analog memory

  • Author

    Linares-Barranco, B. ; Sanchez-Sinencio, E. ; Rodriguez-Vazquez, A. ; Huertas, J.L.

  • Author_Institution
    Texas A&M Univ., College Station, TX, USA
  • fYear
    1991
  • fDate
    11-14 Jun 1991
  • Firstpage
    1283
  • Abstract
    The authors present a complete VLSI continuous-time bidirectional associative memory (BAM). The short term memory (STM) section is implemented using small transconductance four quadrant multipliers, and capacitors for the integrators. The long term memory (LTM) is built using an additional multiplier that uses locally available signals to perform Hebbian learning. The value of the learned weight is present at a capacitor for each synapse. After learning has been accomplished the value of the stored weight voltage can be refreshed using a simple analog/digital (AD)-digital/analog (D/A) conversion, which if done fast enough, will maintain the weight value within a discrete interval of the complete weight range. Such a discretization still allows good performance of the STM section after learning is finished
  • Keywords
    CMOS integrated circuits; VLSI; analogue storage; content-addressable storage; learning systems; neural nets; A/D to D/A conversion; CMOS VLSI; Hebbian learning; VLSI continuous-time bidirectional associative memory; dynamic analog memory; four quadrant multipliers; long term memory; multiplier; on chip learning; short term memory; stored weight voltage; transconductance mode; Analog circuits; Associative memory; Capacitors; Differential equations; Magnesium compounds; Neurons; Subspace constraints; Transconductance; Very large scale integration; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1991., IEEE International Sympoisum on
  • Print_ISBN
    0-7803-0050-5
  • Type

    conf

  • DOI
    10.1109/ISCAS.1991.176604
  • Filename
    176604