Hopfield Neural Network with Double-Layer Amorphous Metal-Oxide Semiconductor Thin-Film Devices as Crosspoint-Type Synapse Elements and Working Confirmation of Letter Recognition

2018 ◽  
pp. 637-646 ◽  
Author(s):  
Mutsumi Kimura ◽  
Kenta Umeda ◽  
Keisuke Ikushima ◽  
Toshimasa Hori ◽  
Ryo Tanaka ◽  
...  
Keyword(s):  
Neural Network ◽  
Thin Film ◽  
Metal Oxide ◽  
Double Layer ◽  
Hopfield Neural Network ◽  
Letter Recognition ◽  
Oxide Semiconductor ◽  
Semiconductor Thin Film ◽  
Amorphous Metal Oxide ◽  
Thin Film Devices

scholarly journals Neuromorphic Chip Integrated with an LSI and Amorphous-metal-oxide Semiconductor Thin-film Synapse Devices

2022 ◽  
Author(s):  
Mutsumi Kimura ◽  
Yuki Shibayama ◽  
Yasuhiko Nakashima
Keyword(s):  
Thin Film ◽  
Metal Oxide ◽  
Digital Circuit ◽  
Amorphous Metal ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Compact Size ◽  
Neuromorphic Systems ◽  
Amorphous Metal Oxide ◽  
Self Learning

Abstract Artificial intelligences are promising in future societies, and neural networks are typical technologies with the advantages such as self-organization, self-learning, parallel distributed computing, and fault tolerance, but their size and power consumption are large. Neuromorphic systems are biomimetic systems from the hardware level, with the same advantages as living brains, especially compact size, low power, and robust operation, but some well-known ones are non-optimized systems, so the above benefits are only partially gained, for example, machine learning is processed elsewhere to download fixed parameters. To solve these problems, we are researching neuromorphic systems from various viewpoints. In this study, a neuromorphic chip integrated with an LSI and amorphous-metal-oxide semiconductor (AOS) thin-film synapse devices has been developed. The neuron elements are digital circuit, which are made in an LSI, and the synapse devices are analog devices, which are made of the AOS thin film and directly integrated on the LSI. This is the world's first hybrid chip where neuron elements and synapse devices of different functional semiconductors are integrated, and local autonomous learning is utilized, which becomes possible because the AOS thin film can be deposited without heat treatment and there is no damage to the underneath layer, and has all advantages of neuromorphic systems.

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