Finite-Level Quantized Iterative Learning Control for a Class of Fuzzy Cellular Neural Networks Based on Encoding-Decoding Mechanism-Reference-Cited by-同舟云学术

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Finite-Level Quantized Iterative Learning Control for a Class of Fuzzy Cellular Neural Networks Based on Encoding-Decoding Mechanism

Published:2023-12-15 Issue: Volume: Page:114-122
ISSN:
Container-title:2023 International Conference on Neuromorphic Computing (ICNC)
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Author:

Yang Yuhan¹,Ma Dan²,Xiong Wenjun³,Li Xichen⁴

Affiliation:

1. Southwestern University of Finance and Economics,School of Statistics,Chengdu,China,611130

2. Southwestern University of Finance and Economics,Center of China Social and Economic Statistical Research,Chengdu,China,611130

3. Southwestern University of Finance and Economics,School of Computing and Artificial Intelligence,Chengdu,China,611130

4. Xihua University,School of Law,Chengdu,China,610039

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10462644/10462727/10462772.pdf?arnumber=10462772

Reference27 articles.

1. The global stability of fuzzy cellular neural network

2. A domain attraction criterion for interval fuzzy neural networks

3. Lagrange exponential stability for fuzzy Cohen–Grossberg neural networks with time-varying delays

4. Finite-time synchronization for fuzzy cellular neural networks with time-varying delays

5. Finite-time stability of a class of fuzzy cellular neural networks with multi-proportional delays

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