Analysis of the Memristor-Based Crossbar Synapse for Neuromorphic Systems
In this study, we analyzed the memristor device typically used as a synapse in neuromorphic architecture and confirmed that the synaptic memristor device can be adopted to perform the machine learning algorithm. The nonlinear characteristics of the memristor complicates its use as the neuromorphic hardware in an artificial neural network (ANN) with a back-propagation algorithm. Using a memristor device with a nonlinear characteristic, we demonstrated that pattern classification can be implemented in ANNs using the Guide training algorithm without back-propagation. Furthermore, the memristor characteristics required to achieve accurate learning results are analyzed.
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Document Type: Research Article
Affiliations: Department of Electronic and Electrical Engineering, Ewha Womans University, 11-1 Daehyun-Dong, Seodaemoon-Gu, Seoul 03760, Republic of Korea
Publication date: October 1, 2019
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