Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4946715 | Neural Networks | 2017 | 21 Pages |
Abstract
This paper focuses on stability analysis for neural networks systems with time-varying delays. A more general auxiliary function-based integral inequality is established and some improved delay-dependent stability conditions formulated in terms of linear matrix inequalities (LMIs) are derived by employing a suitable Lyapunov-Krasovskii functional (LKF) and the novel integral inequality. Three well-known application examples are provided to demonstrate the effectiveness and improvements of the proposed method.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Bin Yang, Juan Wang, Jun Wang,