DocumentCode
3084698
Title
Artificial neural network using thin-film transistors - Working confirmation of asymmetric circuit -
Author
Yamaguchi, Yoshio ; Morita, Ryuji ; Fujita, Yoshikazu ; Miyatani, T. ; Kasakawa, Tomohiro ; Kimura, Mizue
Author_Institution
Dept. of Electron. & Inf., Ryukoku Univ., Otsu, Japan
fYear
2013
fDate
5-6 June 2013
Firstpage
78
Lastpage
79
Abstract
We are developing neural networks of device level using thin-film transistors (TFT). By adopting an interconnect-type neural network and utilizing a characteristic shift of poly-Si TFTs as a variable strength of synapse connection, which was originally an issue, we realized the neuron consisting of eight TFTs and synapse of only one TFT. Particularly in this presentation, we confirmed the working by a circuit where the input and output elements are asymmetric. This is a result leading to a super-large, self-learning, and high-flexibility system.
Keywords
elemental semiconductors; logic circuits; neural nets; silicon; thin film circuits; Si; artificial neural networks; asymmetric circuit; characteristic shift; interconnect-type neural network; poly-Si TFT; synapse connection; thin-film transistor; Biological neural networks; Hebbian theory; Inverters; Neurons; Switches; Thin film transistors; asymmetric circuit; neural network; thin-film transistor (TFT);
fLanguage
English
Publisher
ieee
Conference_Titel
Future of Electron Devices, Kansai (IMFEDK), 2013 IEEE International Meeting for
Conference_Location
Suita
Print_ISBN
978-1-4673-6106-4
Type
conf
DOI
10.1109/IMFEDK.2013.6602249
Filename
6602249
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