Exponential stability of discrete‐time delayed neural networks with saturated impulsive control-Reference-Cited by-同舟云学术

Exponential stability of discrete‐time delayed neural networks with saturated impulsive control

Published:2021-04-16 Issue:12 Volume:15 Page:1628-1645
ISSN:1751-8644
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Appl

Author:

He Zhilong¹²^ORCID,Li Chuandong¹^ORCID,Cao Zhengran¹,Li Hongfei³

Affiliation:

1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing China

2. School of Finance Xinjiang University of Finance and Economics Urumqi China

3. State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science BIC‐ESAT College of Engineering Peking University Beijing China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/cth2.12147

Reference77 articles.

1. A general methodology for designing globally convergent optimization neural networks

2. A General Projection Neural Network for Solving Monotone Variational Inequalities and Related Optimization Problems

3. Solving Pseudomonotone Variational Inequalities and Pseudoconvex Optimization Problems Using the Projection Neural Network

4. Global exponential stability of a general class of recurrent neural networks with time-varying delays

5. Dissipativity Analysis for Stochastic Memristive Neural Networks With Time-Varying Delays: A Discrete-Time Case

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