{"title":"A Robust Control of Fractional Discrete Neural Networks","authors":"Mellah Mohamed, Ouannas Adel","doi":"10.1109/ICRAMI52622.2021.9585959","DOIUrl":null,"url":null,"abstract":"This paper aims to present a general approach to control fractional discrete neural networks. We prove a new theorem, which ensures the stabilization of some fractional discrete neural networks class’s utilzing the Lyapunov approach. A numerical example and simulation results are reported to confirm the stabilization approach efficiency.","PeriodicalId":440750,"journal":{"name":"2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAMI52622.2021.9585959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper aims to present a general approach to control fractional discrete neural networks. We prove a new theorem, which ensures the stabilization of some fractional discrete neural networks class’s utilzing the Lyapunov approach. A numerical example and simulation results are reported to confirm the stabilization approach efficiency.