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http://dx.doi.org/10.5302/J.ICROS.2015.14.8041

Memristor Bridge Synapse-based Neural Network Circuit Design and Simulation of the Hardware-Implemented Artificial Neuron  

Yang, Chang-ju (Division of Electronics and Information Engineering, Chonbuk National University)
Kim, Hyongsuk (Division of Electronics and Information Engineering, Chonbuk National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.5, 2015 , pp. 477-481 More about this Journal
Abstract
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.
Keywords
memristor; memristor bridge synapse; neural network; learning algorithm;
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