Global Mittag-Leffler Stability of Fractional Hopfield Neural Networks with δ-Inverse Hölder Neuron Activations
- 作者: Xiaohong Wang 1, Huaiqin Wu 1
-
隶属关系:
- School of Science, Yanshan University
- 期: 卷 28, 编号 4 (2019)
- 页面: 239-251
- 栏目: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/195235
- DOI: https://doi.org/10.3103/S1060992X19040064
- ID: 195235
如何引用文章
详细
In this paper, the global Mittag-Leffler stability of fractional Hopfield neural networks (FHNNs) with \(\delta \)-inverse hölder neuron activation functions are considered. By applying the Brouwer topological degree theory and inequality analysis techniques, the proof of the existence and uniqueness of equilibrium point is addressed. By constructing the Lure’s Postnikov-type Lyapunov functions, the global Mittag-Leffler stability conditions are achieved in terms of linear matrix inequalities (LMIs). Finally, three numerical examples are given to verify the validity of the theoretical results.
作者简介
Xiaohong Wang
School of Science, Yanshan University
编辑信件的主要联系方式.
Email: xiaohongwangmiao@163.com
中国, Qinhuangdao, 066001
Huaiqin Wu
School of Science, Yanshan University
编辑信件的主要联系方式.
Email: huaiqinwu@ysu.edu.cn
中国, Qinhuangdao, 066001
补充文件
