{"title":"Gradient neural network model for the system of two linear matrix equations and applications","authors":"Jelena Dakić , Marko D. Petković","doi":"10.1016/j.amc.2024.128930","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, the new type of Gradient Neural Network (GNN) model is proposed for the following linear system of matrix equations: <span><math><mi>A</mi><mi>X</mi><mo>=</mo><mi>C</mi><mo>,</mo><mi>X</mi><mi>B</mi><mo>=</mo><mi>D</mi></math></span>. The convergence analysis of given models is shown. The model is applied for the computation of the regular matrix inverse, as well as Moore-Penrose and Drazin generalized inverses. Some illustrative examples and simulations are given to verify theoretical results.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300324003916","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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Abstract
In this paper, the new type of Gradient Neural Network (GNN) model is proposed for the following linear system of matrix equations: . The convergence analysis of given models is shown. The model is applied for the computation of the regular matrix inverse, as well as Moore-Penrose and Drazin generalized inverses. Some illustrative examples and simulations are given to verify theoretical results.
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