Quasi-uniform synchronization of fractional-order memristor-based neural networks with delay

X Yang, C Li, T Huang, Q Song, X Chen - Neurocomputing, 2017 - Elsevier
X Yang, C Li, T Huang, Q Song, X Chen
Neurocomputing, 2017Elsevier
Quasi-uniform synchronization of delayed fractional-order memristor-based neural networks
(FMNNs) is discussed in this paper. On the basis of the theory of fractional differential
equations and the theory of differential inclusion, the synchronization error system between
the concerned drive system and the associated response system is formulated, and then, by
employing Hölder inequality, C p inequality and Gronwall-Bellman inequality, several
sufficient criteria are proposed to ensure the quasi-uniform synchronization for the …
Abstract
Quasi-uniform synchronization of delayed fractional-order memristor-based neural networks (FMNNs) is discussed in this paper. On the basis of the theory of fractional differential equations and the theory of differential inclusion, the synchronization error system between the concerned drive system and the associated response system is formulated, and then, by employing Hölder inequality, Cp inequality and Gronwall-Bellman inequality, several sufficient criteria are proposed to ensure the quasi-uniform synchronization for the considered delayed FMNNs. Three simulation examples are also presented to illustrate the availability and correctness of the theoretical results.
Elsevier
以上显示的是最相近的搜索结果。 查看全部搜索结果