Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407242 | Neurocomputing | 2013 | 7 Pages |
Abstract
This paper concerned with the adaptive synchronization for Takagi–Sugeno (T–S) fuzzy neural networks with stochastic noises and Markovian jumping parameters. By using a new nonnegative function and an M-matrix method, several sufficient conditions are derived to ensure the adaptive synchronization for stochastic T–S fuzzy neural networks. Moreover, the adaptive controller and parameter update laws are designed via adaptive feedback control methods. Finally, a numerical example is given to illustrate the effectiveness of proposed theories.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Dongbing Tong, Qingyu Zhu, Wuneng Zhou, Yuhua Xu, Jian'an Fang,