Affiliation:
1. Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China
Abstract
The issue of robust stability for fractional-order Hopfield neural networks with parameter uncertainties is investigated in this paper. For such neural system, its existence, uniqueness, and global Mittag-Leffler stability of the equilibrium point are analyzed by employing suitable Lyapunov functionals. Based on the fractional-order Lyapunov direct method, the sufficient conditions are proposed for the robust stability of the studied networks. Moreover, robust synchronization and quasi-synchronization between the class of neural networks are discussed. Furthermore, some numerical examples are given to show the effectiveness of our obtained theoretical results.
Funder
National Natural Science Foundation of China
Subject
General Engineering,General Mathematics
Cited by
13 articles.
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