Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
392433 | Information Sciences | 2016 | 12 Pages |
Abstract
This paper is concerned with the L∞ performance analysis problem for time-varying delayed neural networks. First, a condition is proposed for the L∞ performance of single neural networks with time-varying delay and persistent bounded input based on the Wirtinger-type inequality together with the reciprocal convex approach. Then, sufficient conditions are established to ensure the L∞ performance of interconnected neural networks with time-varying delay. Numerical examples are provided to show the effectiveness of the presented results.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Choon Ki Ahn, Peng Shi, Ramesh K. Agarwal, Jing Xu,