AUTHOR=Corti Elisabetta , Cornejo Jimenez Joaquin Antonio , Niang Kham M. , Robertson John , Moselund Kirsten E. , Gotsmann Bernd , Ionescu Adrian M. , Karg Siegfried 

TITLE=Coupled VO2 Oscillators Circuit as Analog First Layer Filter in Convolutional Neural Networks

JOURNAL=Frontiers in Neuroscience

VOLUME=15

YEAR=2021

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2021.628254

DOI=10.3389/fnins.2021.628254

ISSN=1662-453X

ABSTRACT=<p>In this work we present an in-memory computing platform based on coupled VO<sub>2</sub> oscillators fabricated in a crossbar configuration on silicon. Compared to existing platforms, the crossbar configuration promises significant improvements in terms of area density and oscillation frequency. Further, the crossbar devices exhibit low variability and extended reliability, hence, enabling experiments on 4-coupled oscillator. We demonstrate the neuromorphic computing capabilities using the phase relation of the oscillators. As an application, we propose to replace digital filtering operation in a convolutional neural network with oscillating circuits. The concept is tested with a VGG13 architecture on the MNIST dataset, achieving performances of 95% in the recognition task.</p>