DocumentCode
728789
Title
Improvement of learning efficiency in neural network using poly-Si TFTs by synapse TFTs with LDD structure
Author
Morita, Ryohei ; Maeda, Yoshiharu ; Matsuda, Tokiyoshi ; Kimura, Mutsumi
Author_Institution
Dept. of Electron. & Inf., Ryukoku Univ., Otsu, Japan
fYear
2015
fDate
1-4 July 2015
Firstpage
141
Lastpage
142
Abstract
We are developing device-level neural networks using poly-Si TFTs. We succeeded in dramatically reducing the number of transistors in neurons and synapses to integrate a lot of devices, and we also succeeded in actually checking the operation of learning of logics. In this presentation, for the purpose of improvement of learning efficiency, we changed the synapse TFTs from the SD structure to the LDD structure. As a result, we succeeded in improving the learning efficiency by a 5×5 neural network.
Keywords
elemental semiconductors; learning (artificial intelligence); neural nets; silicon; thin film transistors; LDD structure; Si; device-level neural networks; learning efficiency; poly-Si TFT; synapse TFT; Biological neural networks; Degradation; Logic gates; Thin film transistors; Voltage measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Active-Matrix Flatpanel Displays and Devices (AM-FPD), 2015 22nd International Workshop on
Conference_Location
Kyoto
Type
conf
DOI
10.1109/AM-FPD.2015.7173224
Filename
7173224
Link To Document