Stability and Hopf bifurcation analysis of fractional-order complex-valued neural networks with time delays

被引:0
作者
R Rakkiyappan
K Udhayakumar
G Velmurugan
Jinde Cao
Ahmed Alsaedi
机构
[1] Bharathiar University,Department of Mathematics
[2] Southeast University,School of Mathematics and Research Center for Complex Systems and Network Sciences
[3] King Abdulaziz University,Department of Mathematics, Faculty of Science
来源
Advances in Difference Equations | / 2017卷
关键词
Hopfield neural networks; fractional-order; time delays; hub structure; ring structure; stability; Hopf bifurcation;
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摘要
This paper considers a class of fractional-order complex-valued Hopfield neural networks (CVHNNs) with time delay for analyzing the dynamic behaviors such as local asymptotic stability and Hopf bifurcation. In the case of a neural network with hub and ring structure, the stability of the equilibrium state is investigated by analyzing the eigenvalue of the corresponding characteristic matrix for the hub and ring structured fractional-order time delay models using a Laplace transformation for the Caputo-fractional derivatives. Some sufficient conditions are established to guarantee the uniqueness of the equilibrium point. In addition, conditions for the occurrence of a Hopf bifurcation are also presented. Finally, numerical examples are given to demonstrate the effectiveness of the derived results.
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共 115 条
[1]  
Gopalsamy K(1994)Stability in asymmetric Hopfield nets with transmission delays Phys. D: Nonlinear Phenom. 76 344-358
[2]  
He X(2017)Bifurcations in a delayed fractional complex-valued neural network Appl. Math. Comput. 292 210-227
[3]  
Huang C(2002)Fully complex multi layer perceptron network for nonlinear signal processing J. VLSI Signal Process. Syst. Signal Image Video Technol. 32 29-43
[4]  
Cao J(2013)Laplace transform for solving some families of fractional differential equations and its applications Adv. Differ. Equ. 2013 645-665
[5]  
Xiao M(2015)Dissipativity analysis of memristor-based complex-valued neural networks with time-varying delays Inf. Sci. 294 84-97
[6]  
Alsaedi A(2015)Existence and uniform stability analysis of fractional-order complex-valued neural networks with time delays IEEE Trans. Neural Netw. Learn. Syst. 26 42-53
[7]  
Hayat T(2016)Dissipativity and stability analysis of fractional-order complex-valued neural networks with time delay Neural Netw. 86 1089-1092
[8]  
Kim T(2000)Stability analysis of delayed neural networks IEEE Trans. Circuits Syst. I 47 479-500
[9]  
Adali T(2015)Stability analysis of fractional-order neural networks with time delay Neural Process. Lett. 42 141-152
[10]  
Lin S(1985)Neural computation of decisions in optimization problems Biol. Cybern. 52 159-166