Improving the Recognition Accuracy of Memristive Neural Networks via Homogenized Analog Type Conductance Quantization

Improving the Recognition Accuracy of Memristive Neural Networks via Homogenized Analog Type Conductance Quantization

Conductance quantization (QC) phenomena occurring in metal oxide based memristors demonstrate great potential for high-density data storage through multilevel switching, and analog synaptic weight update for effective training of the artificial neural networks. Continuous, linear and symmetrical mod...

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Bibliographic Details
Main Authors: Qilai Chen, Tingting Han, Minghua Tang, Zhang Zhang, Xuejun Zheng, Gang Liu
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Micromachines
Subjects:
memristors
quantum conductance
neural networks
pattern recognition
Online Access:https://www.mdpi.com/2072-666X/11/4/427

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