Global asymptotic stability for discrete-time Cohen-Grossberg neural networks with delays by combining graph theoretic approach with Homeomorphism concept-Reference-Cited by-同舟云学术

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Global asymptotic stability for discrete-time Cohen-Grossberg neural networks with delays by combining graph theoretic approach with Homeomorphism concept

Published:2020-08-12 Issue:6 Volume:33 Page:969-984
ISSN:0952-813X
Container-title:Journal of Experimental & Theoretical Artificial Intelligence
language:en
Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Zhou Zheng¹^ORCID,Liao Huaying²,Zhang Zhengqiu³

Affiliation:

1. School of Applied Mathematics, Xiamen University of Technology, Xiamen, China

2. Department of Mathematics and Computer Science, Nanchang Normal University, Nanchang, China

3. College of Mathematics and Econometrics, Hunan University, Changsha, China

Funder

Science and Technology Research Project of Jiangxi Provincial Education Department

Science and Technology Research Project of Nanchang Normal University

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1801854

Reference42 articles.

1. Global stability analysis of Cohen–Grossberg neural networks with time varying delays

2. Finite-Time Stability of Stochastic Cohen–Grossberg Neural Networks with Markovian Jumping Parameters and Distributed Time-Varying Delays

3. New global asymptotic stability of discrete-time recurrent neural networks with multiple time-varying delays in the leakage term and impulsive effects

4. Existence and stability of periodic solution of high-order discrete-time Cohen–Grossberg neural networks with varying delays

5. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks

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