{"title":"GMRES算法的收敛界","authors":"G. Xie","doi":"10.1109/PDCAT.2003.1236406","DOIUrl":null,"url":null,"abstract":"We first make a brief review of GMRES convergence results. Then we derive new bounds for the GMRES residual norm by making use of a unitary matrix U and a Hermitian positive definite matrix P, which are GMRES-equivalent to the coefficient matrix A with respect to the initial residual r/sub 0/. The existence of such U and P was proved by Leonid (2000). As a GMRES residual norm bound for linear systems with Hermitian positive definite coefficient matrices is known and a GMRES residual norm bound for linear systems with unitary coefficient matrices can be readily derived from Liesen's (2000) work, our new bounds follow from the fact that two GMRES-equivalent matrices make the same residual.","PeriodicalId":145111,"journal":{"name":"Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On convergence bounds of GMRES algorithm\",\"authors\":\"G. Xie\",\"doi\":\"10.1109/PDCAT.2003.1236406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We first make a brief review of GMRES convergence results. Then we derive new bounds for the GMRES residual norm by making use of a unitary matrix U and a Hermitian positive definite matrix P, which are GMRES-equivalent to the coefficient matrix A with respect to the initial residual r/sub 0/. The existence of such U and P was proved by Leonid (2000). As a GMRES residual norm bound for linear systems with Hermitian positive definite coefficient matrices is known and a GMRES residual norm bound for linear systems with unitary coefficient matrices can be readily derived from Liesen's (2000) work, our new bounds follow from the fact that two GMRES-equivalent matrices make the same residual.\",\"PeriodicalId\":145111,\"journal\":{\"name\":\"Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDCAT.2003.1236406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth International Conference on Parallel and Distributed Computing, Applications and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDCAT.2003.1236406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We first make a brief review of GMRES convergence results. Then we derive new bounds for the GMRES residual norm by making use of a unitary matrix U and a Hermitian positive definite matrix P, which are GMRES-equivalent to the coefficient matrix A with respect to the initial residual r/sub 0/. The existence of such U and P was proved by Leonid (2000). As a GMRES residual norm bound for linear systems with Hermitian positive definite coefficient matrices is known and a GMRES residual norm bound for linear systems with unitary coefficient matrices can be readily derived from Liesen's (2000) work, our new bounds follow from the fact that two GMRES-equivalent matrices make the same residual.