Stability analysis of impulsive stochastic reaction-diffusion cellular neural network with distributed delay via fixed point theory
type: Item
instance of: scholarly article
title: Stability analysis of impulsive stochastic reaction-diffusion cellular neural network with distributed delay via fixed point theory
zbMATH Open document ID: 1377.93169
DOI: 10.1155/2017/6292597
published in: Complexity
publication date: 2018-01-05T00:00:00Z
review text: Summary: This paper investigates the stochastically exponential stability of reaction-diffusion impulsive stochastic Cellular Neural Networks (CNN). The reaction-diffusion pulse stochastic system model characterizes the complexity of practical engineering and brings about mathematical difficulties, too. However, the difficulties have been overcome by constructing a new contraction mapping and an appropriate distance on a product space which is guaranteed to be a complete space. This is the first time to employ the fixed-point theorem to derive the stability criterion of reaction-diffusion impulsive stochastic CNN with distributed time delays. Finally, an example is provided to illustrate the effectiveness of the proposed methods.
Mathematics Subject Classification ID: 93E15
Mathematics Subject Classification ID: 93D20
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 90B15
Mathematics Subject Classification ID: 35K57
zbMATH DE Number: 6822324
zbMATH Keywords: stochastically exponential stability
zbMATH Keywords: reaction-diffusion impulsive stochastic cellular neural networks (CNN)
author: Ruofeng Rao
author: Shouming Zhong
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/6292597
OpenAlex ID: W2758158067
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description: scientific article; zbMATH DE number 6822324