Open AccessHighly Uniform All‐Vacuum‐Deposited Inorganic Perovskite Artificial Synapses for Reservoir Computing
Author(s) -
Chen Li-Wei,
Wang Wei-Chun,
Ko Shao-Han,
Chen Chien-Yu,
Hsu Chih-Ting,
Chiao Fu-Ching,
Chen Tse-Wei,
Wu Kai-Chiang,
Lin Hao-Wu
Publication year - 2021
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202170010
Subject(s) - neuromorphic engineering , perovskite (structure) , homogeneous , reservoir computing , halide , materials science , computer science , oxide , nanotechnology , distributed computing , artificial intelligence , optoelectronics , artificial neural network , engineering , physics , chemistry , chemical engineering , inorganic chemistry , metallurgy , recurrent neural network , statistical physics
Uniform Artificial Synapses In article number 2000196 , Kai‐Chiang Wu, Hao‐Wu Lin, and co‐workers demonstrate vacuum deposited halide perovskite devices that exhibit very uniform electrical synaptic characteristics. Utilizing these devices in the reservoir computing can simultaneously reduce the circuitry complexity and increase its recognition accuracy with noisy inputs. The findings promise to facilitate the utilization of highly homogeneous perovskite/metal oxide structures in high‐performance neuromorphic computing systems.