An Interface‐Type Memristive Device for Artificial Synapse and Neuromorphic Computing
Sundar Kunwar, Zachary Jernigan, Zach Hughes, Chase Somodi, Michael Saccone, Francesco Caravelli, Pinku Roy, Di Zhang, Haiyan Wang, Q. X. Jia, Judith L. MacManus‐Driscoll, Garrett T. Kenyon, Andrew Sornborger, Wanyi Nie, Aiping Chen
Abstract
Neuromorphic Computing In article number 2300035, Sundar Kunwar, Aiping Chen, and colleagues present an interface-type resistive switching device with excellent bio-synaptic functionalities. The proposed device exhibits high repeatability, uniformity, and programmability due to the homogeneous control of Schottky contact resistance. The simulated neural network of such a device achieves pattern recognition accuracy of above 94 %, thus offering great potential for neuromorphic computing.
Topics & Concepts
Neuromorphic engineeringInterface (matter)Computer scienceHomogeneousArtificial neural networkResistive touchscreenSynapseArtificial intelligenceMaterials scienceComputer architecturePhysicsParallel computingComputer visionNeuroscienceThermodynamicsBiologyBubbleMaximum bubble pressure methodAdvanced Memory and Neural ComputingCCD and CMOS Imaging SensorsModular Robots and Swarm Intelligence