Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409645 | Neurocomputing | 2015 | 9 Pages |
Abstract
In this paper, global exponential stability of inertial Cohen–Grossberg neural networks with time delays is investigated. By using Homeomorphism theorem and inequality technique, a LMI-based global exponential stability condition and inequality form global exponential stability condition are obtained for the above neural networks. In our result, the assumptions for the differentiability and monotonicity on the behaved functions in Ke and Miao (2013) [23] are removed. Thus our results are less conservative than those obtained in Ke and Miao (2013) [23]. Hence, we obtain new global exponential stability for this neural network.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Shenghua Yu, Zhengqiu Zhang, Zhiyong Quan,