Finite horizon state estimation for time-varying neural networks with sensor failure and energy constraint-Reference-Cited by-同舟云学术

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Finite horizon state estimation for time-varying neural networks with sensor failure and energy constraint

Published:2020-01 Issue: Volume:372 Page:1-7
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Bin,Rao Hongxia,Deng Yunsong,Wu Hao,Zhu Yinxia

Funder

National Natural Science Foundation of China

Science and Technology Planning Project of Guangdong Province

Innovative Research Team Program of Guangdong Province Science Foundation

Department of Education of Guangdong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference27 articles.

1. 30 years of adaptive neural networks: perceptron, madaline, and backpropagation;Widrow;Proc. IEEE,2002

2. H∞ state estimation for artificial neural networks over redundant channels;Zhang;Neurocomputing,2017

3. Adaptive neural network tracking control for robotic manipulators with dead-zone;Zhou;IEEE Trans. Neural Netw. Learn. Syst.,2018

4. Adaptive neural network control of a flexible string system with non-symmetric dead-zone and output constraint;Zhao;Neurocomputing,2018

5. Asynchronous and resilient filtering for Markovian jump neural networks subject to extended dissipativity;Tao;IEEE Trans. Cybern.,2018

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