Analog‐Type Resistive Switching Devices for Neuromorphic Computing-Reference-Cited by-同舟云学术

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Analog‐Type Resistive Switching Devices for Neuromorphic Computing

Published:2019-07-10 Issue:10 Volume:13 Page:1900204
ISSN:1862-6254
Container-title:physica status solidi (RRL) – Rapid Research Letters
language:en
Short-container-title:Phys. Status Solidi RRL

Author:

Zhang Wenbin¹,Gao Bin¹^ORCID,Tang Jianshi¹,Li Xinyi¹,Wu Wei¹,Qian He¹,Wu Huaqiang¹

Affiliation:

1. Institute of MicroelectronicsTsinghua University Beijing 100084 China

Funder

Ministry of Science and Technology of the People's Republic of China

Beijing Innovation Center for Future Chip

Publisher

Wiley

Subject

Condensed Matter Physics,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pssr.201900204

Reference111 articles.

1. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

2. Face classification using electronic synapses

3. Trapping IgE in a closed conformation by mimicking CD23 binding prevents and disrupts FcεRI interaction

4. Equivalent-accuracy accelerated neural-network training using analogue memory

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2. Sophisticated Conductance Control and Multiple Synapse Functions in TiO₂‐Based Multistack‐Layer Crossbar Array Memristor for High‐Performance Neuromorphic Systems;Advanced Functional Materials;2024-06-28

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4. Multifunctional Resistive Switching in a Magnetization-Graded Ni/NiMnIn/V₂O₅ Flexible Heterostructure toward Brain-Inspired Neuromorphic Computing;ACS Applied Electronic Materials;2024-06-06

5. Memristor Crossbar Array with Enhanced Device Yield for In-Memory Vector–Matrix Multiplication;ACS Applied Electronic Materials;2024-05-30

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