{"title":"Global polynomial synchronization of proportional delay memristive neural networks with uncertain parameters and its application to image encryption","authors":"Yan Wan, Liqun Zhou, Jiapeng Han","doi":"10.1016/j.engappai.2025.110290","DOIUrl":null,"url":null,"abstract":"<div><div>This article explores the global polynomial synchronization (GPS) for a type of proportional delay memristive neural networks (PDMNNs), uncertain parameters are considered. First, the theory of differential inclusion is utilized, and then the error system is obtained. Secondly, combining the principles of sliding mode control (SMC) and adaptive control, two different controllers are designed to achieve GPS between the obtained drive–response system. Then, two GPS criteria are obtained through the application of Lyapunov stability theory and inequality analysis techniques. Ultimately, we offer three numerical exemplifications to corroborate the efficacy of the obtained results, along with a demonstration of an application pertaining to image encryption.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"147 ","pages":"Article 110290"},"PeriodicalIF":8.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Applications of Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0952197625002908","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/21 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
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Abstract
This article explores the global polynomial synchronization (GPS) for a type of proportional delay memristive neural networks (PDMNNs), uncertain parameters are considered. First, the theory of differential inclusion is utilized, and then the error system is obtained. Secondly, combining the principles of sliding mode control (SMC) and adaptive control, two different controllers are designed to achieve GPS between the obtained drive–response system. Then, two GPS criteria are obtained through the application of Lyapunov stability theory and inequality analysis techniques. Ultimately, we offer three numerical exemplifications to corroborate the efficacy of the obtained results, along with a demonstration of an application pertaining to image encryption.
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Artificial Intelligence (AI) is pivotal in driving the fourth industrial revolution, witnessing remarkable advancements across various machine learning methodologies. AI techniques have become indispensable tools for practicing engineers, enabling them to tackle previously insurmountable challenges. Engineering Applications of Artificial Intelligence serves as a global platform for the swift dissemination of research elucidating the practical application of AI methods across all engineering disciplines. Submitted papers are expected to present novel aspects of AI utilized in real-world engineering applications, validated using publicly available datasets to ensure the replicability of research outcomes. Join us in exploring the transformative potential of AI in engineering.
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