Journal
APPLIED MATHEMATICS AND COMPUTATION
Volume 313, Issue -, Pages 222-234Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2017.05.078
Keywords
Memristor-based neural network; Complex-valued network; Matrix measure; Lyapunov-Krasovskii functional; Exponential stability
Categories
Funding
- Key Program of Education Department of Sichuan Province [16ZA0066]
- Young scholars development fund of SWPU [201599010003]
- National Natural Science Foundation of China [61573096, 61272530]
- Hong Kong Research Grants Council under Grant City [U 11208515]
Ask authors/readers for more resources
In this paper, we propose a new type of complex-valued memristor-based neural networks with time-varying delays and discuss their exponential stability. Firstly, by using a matrix measure method, the Halanay inequality and some analytic techniques, we derive a sufficient condition for the global exponential stability of this type of neural networks. Then, we build a Lyapunov functional and utilize the Halanay inequality to establish several criteria for the exponential stability of such networks with time-varying delays. Finally, we show two numerical simulations to demonstrate the theoretical results. (C) 2017 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available