Balkan Journal of Electrical and Computer Engineering

2147-284X 2147-284X

MUSA YILMAZ

10.17694/bajece.457902

Engineering

Mühendislik

ANN Circuit Application of Complementary Resistive Switches

Uçar

Erdem

TRAKYA ÜNİVERSİTESİ Karakulak

Ertuğrul

TEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİ Mutlu

Reşat

TEKİRDAĞ NAMIK KEMAL ÜNİVERSİTESİ

01 31 2019

7 1 34 43 09 06 2018 01 18 2019

2013

Balkan Journal of Electrical and Computer Engineering

Artificial neural networks are successfully used for classification,prediction, estimation, modeling and system control. However, artificial neuralnetworks integrated circuits are expensive and not matured enough. Memristorsor memristive systems which show a nonvolatile memory behavior has a highpotential for use in artificial neural network circuit applications. Somememristive synapse or memristive neural network applications already exist inliterature. The complementary memristor or resistive switch memories have beensuggested as an alternative to one-cell memristor memories. Their sensing ismore difficult and complex than the others. The complementary memristor memorytopologies with a sensing node are also inspected in literature. To the best ofour knowledge, a neural network circuit which is based on the complementaryresistive switches with a sensing/writing node does not exist in literatureyet. In this paper, several neuralnetwork circuits which are based on the complementary resistive switches with asensing/writing node have been designed and examined for the first time inliterature. Their analysis are given and simulations are performed to verifytheir operation. We expect that such a complementary resistive switchimplementation may find use in artificial neural networks chips in the future.

Memristor Memristive systems Complementary resistive switches Artificial neural networks ANN circuits

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