{"title":"修正共轭梯度法的收敛性","authors":"Bo Zhang","doi":"10.1109/CINC.2010.5643723","DOIUrl":null,"url":null,"abstract":"In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Convergence of modified conjugate gradient methods without line search\",\"authors\":\"Bo Zhang\",\"doi\":\"10.1109/CINC.2010.5643723\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643723\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643723","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convergence of modified conjugate gradient methods without line search
In this paper, a class of modified conjugate gradient methods are proposed, which have the following attractive properties: (1) the step length is determined by a formula; (2) the iterative direction is always a sufficient descent direction without utilizing the line search. Under the boundedness of the level set and the Lipschitz continuity of the underlying function, the proposed methods are global convergent. Some numerical results are given to illustrate the effectiveness of the proposed methods.