A new result on H∞ performance state estimation for static neural networks with time-varying delays-Reference-Cited by-同舟云学术

A new result on H∞ performance state estimation for static neural networks with time-varying delays

Published:2021-01 Issue: Volume:388 Page:125556
ISSN:0096-3003
Container-title:Applied Mathematics and Computation
language:en
Short-container-title:Applied Mathematics and Computation

Author:

Tian Yufeng,Wang Zhanshan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference38 articles.

1. Fuzzy adaptive event-triggered sampled-data control for stabilization of T-S fuzzy memristive neural networks with reaction-diffusion terms;Zhang;IEEE Trans. Fuzzy Syst.,2020

2. Quantized sampled-data control for synchronization of inertial neural networks with heterogeneous time-varying delays;Zhang;IEEE Trans. Neural Netw. Learn. Syst.,2018

3. Prediction and identification of discrete-time dynamic nonlinear systems based on adaptive echo state network;Yao;Neural Netw.,2019

4. h∞ performance state estimation for static neural networks with time-varying delays via two improved inequalities;Tian;IEEE Trans. Circuits Syst. II,2020

5. Event-triggered synchronization of discrete-time neural networks: a switching approach;Ding;Neural Netw.,2020

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