Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6863241 | Neural Networks | 2016 | 15 Pages |
Abstract
The present paper is devoted to investigating the global dissipativity for inertial neural networks with time-varying delays and parameter uncertainties. By virtue of a suitable substitution, the original system is transformed to the first order differential system. By means of matrix measure, generalized Halanay inequality, and matrix-norm inequality, several sufficient criteria for the global dissipativity of the addressed neural networks are proposed. Meanwhile, the specific estimations of positive invariant sets and globally attractive sets are obtained. Finally, two examples are provided to validate our theoretical results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhengwen Tu, Jinde Cao, Tasawar Hayat,