期刊论文

Huang, Chuangxia

英文

Journal of Experimental & Theoretical Artificial Intelligence

0952-813X

2020

32

1

133-146

10.1080/0952813X.2019.1635654

This work was supported by the National Natural Science Foundation of China (Nos. 11861037, 71471020, 51839002), the Hunan Provincial Natural Science Foundation of China (No. 2016JJ1001), and the Scientific Research Fund of Hunan Provincial Education Department (No. 15A003). The author would like to express the sincere appreciation to the editors and anonymous reviewers for their constructive comments and suggestions which helped to improve the present paper.

本校为第一且通讯机构

This paper studies a class of inertial neural networks involving proportional delays. Without adopting reduced order method, by combining Lyapunov function method with differential inequality approach, some novel assertions are gained to validate the global generalised exponential stability of the addressed model, which are new and complement some previous works. In the end, some examples with their numerical simulations are carried out ...