Global Mittag-Leffler Stability of Fractional Hopfield Neural Networks with δ-Inverse Holder Neuron Activations

被引：0
|
作者：
Wang, Xiaohong [1 ]
Wu, Huaiqin [1 ]
机构：
[1] Yanshan Univ, Sch Sci, Qinhuangdao 066001, Hebei, Peoples R China
来源：
OPTICAL MEMORY AND NEURAL NETWORKS | 2019年 / 28卷 / 04期
关键词：
fractional neural networks; global Mittag-Leffler stability; delta-inverse Holder functions; Lur'e Postnikov-type Lyapunov functional; topological degree; FINITE-TIME; SYNCHRONIZATION;
D O I：
10.3103/S1060992X19040064
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper, the global Mittag-Leffler stability of fractional Hopfield neural networks (FHNNs) with delta-inverse holder 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.
引用
收藏
页码：239 / 251
页数：13
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