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Time-Delay Encoded Image Recognition in a Network of Resistively Coupled VO₂ on Si Oscillators

Elisabetta Corti, Abhishek Khanna, Kham M. Niang, John Robertson, Kirsten E. Moselund, Bernd Gotsmann, Suman Datta, Siegfried Karg

2020IEEE Electron Device Letters47 citationsDOIOpen Access PDF

Abstract

Oscillatory neural networks based on insulator to metal transition of VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> switches are implemented for image recognition. The VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> oscillators are fabricated on silicon in a CMOS compatible process. A fully-connected network of coupled oscillators is investigated using programmable resistors as coupling elements. In this approach, input of the image information and data processing is performed in the time domain. In particular, tuning the coupling resistors allows to control the phase-relation between the oscillators. This is used to memorize and recognize patterns in an analog circuit. The concept is demonstrated experimentally on a three-VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> oscillator network, whereas simulations are performed on a larger 9-oscillators circuit.

Topics & Concepts

ResistorArtificial neural networkComputer scienceCorydalisCoupling (piping)Topology (electrical circuits)CMOSElectronic engineeringElectrical engineeringArtificial intelligenceEngineeringVoltageMedicineAlternative medicinePathologyMechanical engineeringTraditional Chinese medicineAdvanced Memory and Neural ComputingNeural Networks and Reservoir ComputingTransition Metal Oxide Nanomaterials
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