{"title":"Exponential stability of infinite-dimensional impulsive stochastic systems with Poisson jumps under aperiodically intermittent control","authors":"Yiqun Liu, Lili Chen, Yanfeng Zhao, Zhen Wang","doi":"10.1016/j.neunet.2025.107331","DOIUrl":null,"url":null,"abstract":"<div><div>This paper studies the problem of mean square exponential stability (ES) for a class of impulsive stochastic infinite-dimensional systems with Poisson jumps (ISIDSP) using aperiodically intermittent control (AIC). It provides a detailed analysis of impulsive disturbances, and the related inequalities are given for the two cases when the impulse perturbation occurs at the start time points of the control and rest intervals or non-startpoints, respectively. Additionally, in virtue of Yosida approximating systems, combining with the Lyapunov method, graph theory and the above inequalities, criteria for ES of the above impulsive stochastic infinite-dimensional systems are established under AIC for these two perturbation scenarios. These criteria elucidate the effects of the impulsive perturbation strength, the ratio of control period, to rest period, and network topology on ES. Finally, the theoretical results are applied to a class of neural networks with reaction–diffusion processes, and the effectiveness of the findings is validated through numerical simulations.</div></div>","PeriodicalId":49763,"journal":{"name":"Neural Networks","volume":"187 ","pages":"Article 107331"},"PeriodicalIF":6.0000,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0893608025002102","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the problem of mean square exponential stability (ES) for a class of impulsive stochastic infinite-dimensional systems with Poisson jumps (ISIDSP) using aperiodically intermittent control (AIC). It provides a detailed analysis of impulsive disturbances, and the related inequalities are given for the two cases when the impulse perturbation occurs at the start time points of the control and rest intervals or non-startpoints, respectively. Additionally, in virtue of Yosida approximating systems, combining with the Lyapunov method, graph theory and the above inequalities, criteria for ES of the above impulsive stochastic infinite-dimensional systems are established under AIC for these two perturbation scenarios. These criteria elucidate the effects of the impulsive perturbation strength, the ratio of control period, to rest period, and network topology on ES. Finally, the theoretical results are applied to a class of neural networks with reaction–diffusion processes, and the effectiveness of the findings is validated through numerical simulations.
期刊介绍:
Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.