ANN Circuit Application of Complementary Resistive Switches

Year 2019, Volume: 7 Issue: 1, 34 - 43, 31.01.2019

Erdem Uçar , Ertuğrul Karakulak , Reşat Mutlu

https://doi.org/10.17694/bajece.457902

Cited By: 1

Abstract

Artificial neural networks are successfully used for classification,
prediction, estimation, modeling and system control. However, artificial neural
networks integrated circuits are expensive and not matured enough. Memristors
or memristive systems which show a nonvolatile memory behavior has a high
potential for use in artificial neural network circuit applications. Some
memristive synapse or memristive neural network applications already exist in
literature. The complementary memristor or resistive switch memories have been
suggested as an alternative to one-cell memristor memories. Their sensing is
more difficult and complex than the others. The complementary memristor memory
topologies with a sensing node are also inspected in literature. To the best of
our knowledge, a neural network circuit which is based on the complementary
resistive switches with a sensing/writing node does not exist in literature
yet.  In this paper, several neural
network circuits which are based on the complementary resistive switches with a
sensing/writing node have been designed and examined for the first time in
literature. Their analysis are given and simulations are performed to verify
their operation. We expect that such a complementary resistive switch
implementation may find use in artificial neural networks chips in the future.

Keywords

Memristor, Memristive systems, Complementary resistive switches, Artificial neural networks, ANN circuits

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