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A ferroelectric memristor with a capacitor-like structure for neuromorphic computing
This paper presents a ferroelectric memristor-based synaptic device with a capacitor-like structure and nonvolatile multilevel conductance. Conductance modulation can be achieved by manipulating the barrier height through polarization inversion and the mimicking of the important synaptic functions,...
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Published in: | Journal of physics. D, Applied physics Applied physics, 2023-03, Vol.56 (12), p.125302 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper presents a ferroelectric memristor-based synaptic device with a capacitor-like structure and nonvolatile multilevel conductance. Conductance modulation can be achieved by manipulating the barrier height through polarization inversion and the mimicking of the important synaptic functions, such as long-term plasticity and spike-timing-dependent plasticity, have been implemented. By extracting device parameters, a simulated artificial neural network is constructed for image recognition, and it can achieve 91.2% recognition accuracy for Modified National Institute of Standards and Technology images. These results show the potential of this device in building brain-like computing systems and further enrich the research of ferroelectric materials in realizing artificial synapses. |
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ISSN: | 0022-3727 1361-6463 |
DOI: | 10.1088/1361-6463/acbb12 |