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
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);
Conference_Titel :
Future of Electron Devices, Kansai (IMFEDK), 2013 IEEE International Meeting for
Conference_Location :
Suita
Print_ISBN :
978-1-4673-6106-4
DOI :
10.1109/IMFEDK.2013.6602249