Research Article, J Electr Eng Electron Technol Vol: 6 Issue: 1
Simplification of Processing Elements in Cellular Neural Network
| Mutsumi Kimura1,2*,Hiroki Nakanishi2, Nao Nakamura2, Tomoharu Yokoyama2, Tokiyoshi Matsuda2, Tomoya Kameda2 and Yasuhiko Nakashima1 | |
| 1Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, 630-0192, Japan | |
| 2Departments of Electronics and Informatics, Ryukoku University, Otsu, 520- 2194, Japan | |
| Corresponding author : Mutsumi KIMURA Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, 630-0192, Japan Tel: 077-543-7407 E-mail: mutsu@rins.ryukoku.ac.jp |
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| Received: March 30, 2017 Accepted: April 11, 2017 Published: April 18, 2017 | |
| Citation: Kimura M, Nakanishi H, Nakamura N, Yokoyama T, Matsuda T, et al. (2017) Simplification of Processing Elements in Cellular Neural Network. J Electr Eng Electron Technol 6:1. doi: 10.4172/2325-9833.1000137 |
Abstract
We have succeeded in simplification of processing elements in cellular neural network. First, we reduce a neuron to two-inverter two-switch circuit, two-inverter one-switch circuit, or two-inverter circuit. Next, we reduce a synapse only to one variable resistor or one variable capacitor. Finally, we confirm the correct operation of the cellular neural network by learning of arbitrary logics. These results will be theoretical bases to realize ultra-large scale integration for brain-type integrated circuits.
