Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1866057 | Physics Letters A | 2008 | 8 Pages |
Abstract
This Letter studies synchronization of delayed fuzzy cellular neural networks with all the parameters unknown. To enhance the coupled strength dynamically and be more suitable for the reality, we add fuzzy theory to the traditional cellular neural networks. By the Lyapunov–Lasall principle of functional differential equations, some new stability criteria are obtained via adaptive control. To the best of our knowledge, there has few work studying fuzzy cellular neural networks. Moreover, the approaches developed here extend the ideas and techniques derived in recent literatures. In the end, an example and its simulation were given to illustrate the simpleness and effectiveness of our main results.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Physics and Astronomy (General)
Authors
Wei Ding, Maoan Han,