A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning-Reference-Cited by-同舟云学术

A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning

Published:2023-10 Issue:5 Volume:17 Page:1153-1165
ISSN:1932-4545
Container-title:IEEE Transactions on Biomedical Circuits and Systems
language:
Short-container-title:IEEE Trans. Biomed. Circuits Syst.

Author:

Wang Deyu¹^ORCID,Xu Jiawei²^ORCID,Li Feng¹^ORCID,Zhang Lianhao³,Cao Chengwei¹,Stathis Dimitrios⁴,Lansner Anders⁴^ORCID,Hemani Ahmed⁴^ORCID,Zheng Li-Rong⁵^ORCID,Zou Zhuo¹^ORCID

Affiliation:

1. State Key Laboratory of Integrated Chips and Systems, School of Information Science and Technology, Fudan University, Shanghai, China

2. Guangdong Institute of Intelligence Science and Technology, Zhuhai, China

3. Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark

4. School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden

5. School of Information Science and Technology, Fudan University, Shanghai, China

Funder

Key-Area Research and Development Program of Guangdong Province

NSFC-STINT joint project

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/4156126/10325378/10169114.pdf?arnumber=10169114

Reference48 articles.

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3. An memristor-based synapse implementation using BCM learning rule

4. Optimizing BCPNN Learning Rule for Memory Access

5. Unsupervised learning of digit recognition using spike-timing-dependent plasticity

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