{"title":"Robust Sampled-Data Synchronization of Memristor Inertial Competitive Neural Networks With Two Delay Components","authors":"A. R. Subhashri, T. Radhika","doi":"10.1002/mma.10713","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The current study addresses the issue of synchronization in competitive neural networks that are based on memristors and involve an inertial term, parameter uncertainty, and two delay components using sampled-data control. To achieve synchronization, appropriate Lyapunov-Krasovskii functionals (LKFs) are constructed, which include double and triple integral terms that capture the information of time delay cross terms. Some sufficient synchronization conditions are derived in terms of linear matrix inequalities (LMIs) using an improved reciprocally convex combination inequality and generalized free weighting matrices inequality. The effectiveness of the proposed findings is highlighted through an illustrative example, validating the robustness and reliability of the developed synchronization approach.</p>\n </div>","PeriodicalId":49865,"journal":{"name":"Mathematical Methods in the Applied Sciences","volume":"48 6","pages":"6764-6778"},"PeriodicalIF":2.1000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Methods in the Applied Sciences","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/mma.10713","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The current study addresses the issue of synchronization in competitive neural networks that are based on memristors and involve an inertial term, parameter uncertainty, and two delay components using sampled-data control. To achieve synchronization, appropriate Lyapunov-Krasovskii functionals (LKFs) are constructed, which include double and triple integral terms that capture the information of time delay cross terms. Some sufficient synchronization conditions are derived in terms of linear matrix inequalities (LMIs) using an improved reciprocally convex combination inequality and generalized free weighting matrices inequality. The effectiveness of the proposed findings is highlighted through an illustrative example, validating the robustness and reliability of the developed synchronization approach.
期刊介绍：
Mathematical Methods in the Applied Sciences publishes papers dealing with new mathematical methods for the consideration of linear and non-linear, direct and inverse problems for physical relevant processes over time- and space- varying media under certain initial, boundary, transition conditions etc. Papers dealing with biomathematical content, population dynamics and network problems are most welcome.
Mathematical Methods in the Applied Sciences is an interdisciplinary journal: therefore, all manuscripts must be written to be accessible to a broad scientific but mathematically advanced audience. All papers must contain carefully written introduction and conclusion sections, which should include a clear exposition of the underlying scientific problem, a summary of the mathematical results and the tools used in deriving the results. Furthermore, the scientific importance of the manuscript and its conclusions should be made clear. Papers dealing with numerical processes or which contain only the application of well established methods will not be accepted.
Because of the broad scope of the journal, authors should minimize the use of technical jargon from their subfield in order to increase the accessibility of their paper and appeal to a wider readership. If technical terms are necessary, authors should define them clearly so that the main ideas are understandable also to readers not working in the same subfield.
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