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Memristive operational amplifiers

  • Timur Ibrayev
  • , Irina Fedorova
  • , Akshay Kumar Maan
  • , Alex Pappachen James
    • Nazarbayev University
    • Griffith University Queensland
    • Enview R and D Labs

    Research output: Contribution to journalConference articlepeer-review

    Abstract

    The neuronal algorithms process the information coming from the natural environment in analog domain at sensory processing level and convert the signals to digital domain before performing cognitive processing. The weighting of the signals is an inherent way the neurons tell the brain on the importance of the inputs and digitisation using threshold logic the neurons way to make low level decisions from it. The analogue implementation of the weighted multiplication to input responses is essentially an amplification operation and so is the threshold logic comparator that can be implemented using amplifiers. In this sense, amplifiers are essential building in the development of threshold logic computing architectures. Specifically, operational amplifier would act as the best candidate for use with threshold logic circuits due to its useful properties of large gain, low output resistance and high input resistance. In this paper, a reconfigurable operational amplifier is proposed based on quantised conductance devices in combination with MOSFET devices. The designed amplifier is used to design a threshold logic cell that has the capability to work as different logic gates. The presented quantised conductance memristive operational amplifier show promising performance results in terms of power dissipation, on-chip area and THD values.

    Original languageEnglish
    Pages (from-to)114-119
    Number of pages6
    JournalProcedia Computer Science
    Volume41
    DOIs
    Publication statusPublished - 2014
    Event5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014 - Cambridge, United States
    Duration: Nov 7 2014Nov 9 2014

    Keywords

    • Amplifiers
    • Memristors
    • Neuromorphic computing
    • Threshold logic

    ASJC Scopus subject areas

    • General Computer Science

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