<i>L</i><sub>2</sub>-<i>L</i><sub>∞</sub> state estimation for continuous stochastic delayed neural networks via memory event-triggering strategy-Reference-Cited by-同舟云学术

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L₂-L_∞ state estimation for continuous stochastic delayed neural networks via memory event-triggering strategy

Published:2022-04-06 Issue:13 Volume:53 Page:2742-2757
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Yang Juanjuan¹,Ma Lifeng¹^ORCID,Chen Yonggang²,Yi Xiaojian³

Affiliation:

1. School of Automation, Nanjing University of Science and Technology, Nanjing, People's Republic of China

2. School of Mathematical Sciences, Henan Institute of Science and Technology, Xinxiang, People's Republic of China

3. School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, People's Republic of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2022.2055192

Reference54 articles.

1. State estimation for switched discrete-time stochastic BAM neural networks with time varying delay

2. Deep neural networks learn by using human-selected electrocardiogram features and novel features

3. sEMG pattern recognition based on recurrent neural network

4. Further results on passivity analysis of delayed neural networks with leakage delay

5. Stochastic stability for distributed delay neural networks via augmented Lyapunov–Krasovskii functionals

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