Memristive Operational Amplifiers

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Ibrayev, Timur
Fedorova, Irina
Maan, Akshay
Pappachen James, Alex
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2014
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https://creativecommons.org/licenses/by-nc-nd/3.0/
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.

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Procedia Computer Science
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41
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© 2014 The Authors. Published by Elsevier Ltd. . This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
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Information and Computing Sciences not elsewhere classified
Information and Computing Sciences
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