- Volume 21 Issue 5
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Memristor Bridge Synapse-based Neural Network Circuit Design and Simulation of the Hardware-Implemented Artificial Neuron
멤리스터 브리지 시냅스 기반 신경망 회로 설계 및 하드웨어적으로 구현된 인공뉴런 시뮬레이션
- Yang, Chang-ju (Division of Electronics and Information Engineering, Chonbuk National University) ;
- Kim, Hyongsuk (Division of Electronics and Information Engineering, Chonbuk National University)
- Received : 2014.11.24
- Accepted : 2015.01.30
- Published : 2015.05.01
Implementation of memristor-based multilayer neural networks and their hardware-based learning architecture is investigated in this paper. Two major functions of neural networks which should be embedded in synapses are programmable memory and analog multiplication. "Memristor", which is a newly developed device, has two such major functions in it. In this paper, multilayer neural networks are implemented with memristors. A Random Weight Change algorithm is adopted and implemented in circuits for its learning. Its hardware-based learning on neural networks is two orders faster than its software counterpart.
Supported by : 한국연구재단
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