An extremely low-power-consumption reconfigurable two-dimensional tellurene artificial synapse for bio-inspired wearable edge computing
Bolim You, Jeechan Yoon, Yuna Kim, Mino Yang, Jina Bak, Jihyang Park, Un Jeong Kim, Myung Gwan Hahm, Moonsang Lee
Abstract
We fabricated a reconfigurable two-dimensional tellurene artificial synaptic transistor on a flexible substrate for bio-inspired wearable neuromorphic edge computing, showing an extremely low power consumption of 9 fJ and an impressive accuracy of 93% in recognizing MNIST patterns.
Topics & Concepts
Neuromorphic engineeringMNIST databaseMaterials sciencePower consumptionWearable computerEnhanced Data Rates for GSM EvolutionTransistorSubstrate (aquarium)Edge computingSynapseWearable technologyPower (physics)Computer scienceNanotechnologyComputer architectureOptoelectronicsArtificial neural networkElectronic engineeringArtificial intelligenceEmbedded systemElectrical engineeringEngineeringNeurosciencePhysicsBiologyVoltageEcologyQuantum mechanicsAdvanced Memory and Neural Computing2D Materials and ApplicationsConducting polymers and applications