Publication | Open Access
Time-Delay Encoded Image Recognition in a Network of Resistively Coupled VO₂ on Si Oscillators
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Citations
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References
2020
Year
EngineeringOscillatorsNeural Networks (Machine Learning)Integrated CircuitsSi OscillatorsSocial SciencesCoupling ResistorsNeuromorphic EngineeringNeuromorphic DevicesElectronic CircuitElectrical EngineeringPhysicsComputer EngineeringProgrammable ResistorsNeural Networks (Computational Neuroscience)MicroelectronicsOscillatory Neural NetworksApplied PhysicsResistively Coupled Vo₂
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.
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