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Simplification of Processing Elements in Cellular Neural Networks - Working Confirmation Using Circuit Simulation.

, , , , , and . ICONIP (2), volume 9948 of Lecture Notes in Computer Science, page 309-317. (2016)

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Simplification of Processing Elements in Cellular Neural Networks - Working Confirmation Using Circuit Simulation., , , , , and . ICONIP (2), volume 9948 of Lecture Notes in Computer Science, page 309-317. (2016)Letter Reproduction Simulator for Hardware Design of Cellular Neural Network Using Thin-Film Synapses - Crosspoint-Type Synapses and Simulation Algorithm., , and . ICONIP (2), volume 9948 of Lecture Notes in Computer Science, page 342-350. (2016)CPU Meets VR: A Scalable 3D Representation of Manycores for Behavior Analysis., , , , , , and . CANDAR, page 375-380. IEEE Computer Society, (2016)Cellular neural network formed by simplified processing elements composed of thin-film transistors., , , , , and . Neurocomputing, (2017)Neuromorphic Hardware Using Simplified Elements and Thin-Film Semiconductor Devices as Synapse Elements - Simulation of Hopfield and Cellular Neural Network -., , and . ICONIP (6), volume 10639 of Lecture Notes in Computer Science, page 769-776. Springer, (2017)Neuro-inspired System with Crossbar Array of Amorphous Metal-Oxide-Semiconductor Thin-Film Devices as Self-plastic Synapse Units., , , , , , , and . ICONIP (2), volume 11954 of Lecture Notes in Computer Science, page 481-491. Springer, (2019)Hopfield Neural Network with Double-Layer Amorphous Metal-Oxide Semiconductor Thin-Film Devices as Crosspoint-Type Synapse Elements and Working Confirmation of Letter Recognition., , , , , , , and . ICONIP (7), volume 11307 of Lecture Notes in Computer Science, page 637-646. Springer, (2018)