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Environment-Adaptable Artificial Visual Perception Behaviors Using a Light-Adjustable Optoelectronic Neuromorphic Device Array

delete2019-11-14
delete258
PRE
AI
S
Sung Min Kwon
S
Sung Woon Cho
M
Min‐Ho Kim
J
Jae Sang Heo
Y
Yong‐Hoon Kim *
S
Sung Kyu Park *
DOI:10.1002/adma.201906433delete
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摘要

摘要

En 中文
Emulating the biological visual perception system typically requires a complex architecture including the integration of an artificial retina and optic nerves with various synaptic behaviors. However, self-adaptive synaptic behaviors, which are frequently translated into visual nerves to adjust environmental light intensities, have been one of the serious challenges for the artificial visual perception system. Here, an artificial optoelectronic neuromorphic device array to emulate the light-adaptable synaptic functions (photopic and scotopic adaptation) of the biological visual perception system is presented. By employing an artificial visual perception circuit including a metal chalcogenide photoreceptor transistor and a metal oxide synaptic transistor, the optoelectronic neuromorphic device successfully demonstrates diverse visual synaptic functions such as phototriggered short-term plasticity, long-term potentiation, and neural facilitation. More importantly, the environment-adaptable perception behaviors at various levels of the light illumination are well reproduced by adjusting load transistor in the circuit, exhibiting the acts of variable dynamic ranges of biological system. This development paves a new way to fabricate an environmental-adaptable artificial visual perception system with profound implications for the field of future neuromorphic electronics.
Keyword:
artificial retinas
artificial vision systems
ionotronic synaptic transistors
light-adjustable neuromorphic circuits
photopic and scotopic adaptation
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Advanced Materials 封面图
Advanced Materials
IF:
26.8
论文数:
3.4W
被引数:
46.0W

机构

S
sungkyunkwan university (skku)
学者数:
3.7W
论文数: 3.6W
被引数: 49
C
Chung Ang University
学者数:
1.3W
论文数: 1.4W
被引数: 133
U
University of Connecticut
学者数:
2.4W
论文数: 2.2W
被引数: 2.5W
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