Coexistence of Cyclic Sequential Pattern Recognition and Associative Memory in Neural Networks by Attractor Mechanisms-Reference-Cited by-同舟云学术

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Coexistence of Cyclic Sequential Pattern Recognition and Associative Memory in Neural Networks by Attractor Mechanisms

Published:2024 Issue: Volume: Page:1-12
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Huo Jingyang¹,Yu Jiali¹^ORCID,Wang Min²,Yi Zhang³^ORCID,Leng Jinsong¹,Liao Yong⁴

Affiliation:

1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China

2. School of Mathematics and Statistics, Ludong University, Yantai, China

3. College of Computer Science, Sichuan University, Chengdu, China

4. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10459336.pdf?arnumber=10459336

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning sequence attractors in recurrent networks with hidden neurons;Neural Networks;2024-10

2. Attractors coexistence and representation research of Lotka–Volterra recurrent neural networks by matrix analysis theory;Neurocomputing;2024-09

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