Dynamical Behavior of Complex-Valued Hopfield Neural Networks with Discontinuous Activation Functions

被引:0
|
作者
Zengyun Wang
Zhenyuan Guo
Lihong Huang
Xinzhi Liu
机构
[1] Hunan First Normal University,Department of Mathematics
[2] Hunan University,College of Mathematics and Econometrics
[3] Changsha University of Science and Technology,Department of Applied Mathematics
[4] University of Waterloo,undefined
来源
Neural Processing Letters | 2017年 / 45卷
关键词
Discontinuous complex-valued Hopfield neural network; Global stability; Convergence in finite time; Differential inclusion; Filippov solution;
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学科分类号
摘要
This paper presents some theoretical results on dynamical behavior of complex-valued neural networks with discontinuous neuron activations. Firstly, we introduce the Filippov differential inclusions to complex-valued differential equations with discontinuous right-hand side and give the definition of Filippov solution for discontinuous complex-valued neural networks. Secondly, by separating complex-valued neural networks into real and imaginary part, we study the existence of equilibria of the neural networks according to Leray–Schauder alternative theorem of set-valued maps. Thirdly, by constructing appropriate Lyapunov function, we derive the sufficient condition to ensure global asymptotic stability of the equilibria and convergence in finite time. Numerical examples are given to show the effectiveness and merits of the obtained results.
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页码:1039 / 1061
页数:22
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