Journal
NONLINEAR ANALYSIS-HYBRID SYSTEMS
Volume 16, Issue -, Pages 104-121Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.nahs.2014.10.001
Keywords
Fractional-order; Neural networks; Mittag-Leffler stability; The second method of Lyapunov; Synchronization
Categories
Funding
- National Nature Science Foundation of China [11371049]
Ask authors/readers for more resources
Fractional-order Hopfield neural networks are often used to model how interacting neurons process information. To show reliability of the processed information, it is needed to perform stability analysis of these systems. Here, we perform Mittag-Leffler stability analysis for them. For this, we extend the second method of Lyapunov in the fractional-order case and establish a useful inequality that can be effectively used to this analysis. Importantly, these general results can help construct Lyapunov functions used to Mittag-Leffler stability analysis of fractional-order Hopfield neural networks. As a result, a set of sufficient conditions is derived to guarantee this stability. In addition, the general results can be easily used to the establishment of stability conditions for achieving complete and quasi synchronization in the coupling case of these networks with constant or time-dependent external inputs. Finally, two numerical examples are presented to show the effectiveness of our theoretical results. (C) 2014 Elsevier Ltd. 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