Robust asymptotical stability and stabilization of fractional-order complex-valued neural networks with delay
type: Item
instance of: scholarly article
title: Robust asymptotical stability and stabilization of fractional-order complex-valued neural networks with delay
zbMATH Open document ID: 1486.34043
DOI: 10.1155/2021/5653791
author: Xujun Yang
author: Lu Wang
author: Xiaofeng Chen
author: JingJing Zeng
published in: Discrete Dynamics in Nature and Society
publication date: 2022-01-11T00:00:00Z
review text: Summary: The robust asymptotical stability and stabilization for a class of fractional-order complex-valued neural networks (FCNNs) with parametric uncertainties and time delay are considered in this paper. It is worth noting that our system combines complex numbers, uncertain parameters, time delay, and fractional orders, which is universal in practical application. Using the theorem of homeomorphism, the sufficient condition of the existence and uniqueness of the equilibrium point for the system is obtained. Then, the sufficient criteria of robust asymptotical stability and stabilization for the addressed models are established, respectively. Finally, we give two numerical examples to verify the feasibility and effectiveness of the theoretical results.
Mathematics Subject Classification ID: 34A08
Mathematics Subject Classification ID: 34K37
Mathematics Subject Classification ID: 34D20
zbMATH DE Number: 7455404
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/5653791
OpenAlex ID: W3212536307
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description: scientific article; zbMATH DE number 7455404