{"title":"高斯消去的三个奥秘","authors":"L. Trefethen","doi":"10.1145/1057954.1057955","DOIUrl":null,"url":null,"abstract":"If numerical analysts understand anything, surely it must be Gaussian elimination. This is the oldest and truest of numerical algorithms. To be precise, I am speaking of Gaussian elimination with partial pivoting, the universal method for solving a dense, unstructured n X n linear system of equations Ax = b on a serial computer. This algorithm has been so successful that to many of us, Gaussian elimination and Ax = b are more or less synonymous. The chapter headings in the book by Golub and Van Loan [3] are typical -- along with \"Orthogonalization and Least Squares Methods,\" \"The Symetric Eigenvalue Problem,\" and the rest, one finds \"Gaussian Elimination,\" not \"Linear Systems of Equations.\"","PeriodicalId":177516,"journal":{"name":"ACM Signum Newsletter","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1985-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Three mysteries of Gaussian elimination\",\"authors\":\"L. Trefethen\",\"doi\":\"10.1145/1057954.1057955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"If numerical analysts understand anything, surely it must be Gaussian elimination. This is the oldest and truest of numerical algorithms. To be precise, I am speaking of Gaussian elimination with partial pivoting, the universal method for solving a dense, unstructured n X n linear system of equations Ax = b on a serial computer. This algorithm has been so successful that to many of us, Gaussian elimination and Ax = b are more or less synonymous. The chapter headings in the book by Golub and Van Loan [3] are typical -- along with \\\"Orthogonalization and Least Squares Methods,\\\" \\\"The Symetric Eigenvalue Problem,\\\" and the rest, one finds \\\"Gaussian Elimination,\\\" not \\\"Linear Systems of Equations.\\\"\",\"PeriodicalId\":177516,\"journal\":{\"name\":\"ACM Signum Newsletter\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1985-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Signum Newsletter\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1057954.1057955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Signum Newsletter","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1057954.1057955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
摘要
如果数值分析家理解什么,那肯定是高斯消去法。这是最古老、最真实的数值算法。准确地说,我说的是带有部分枢轴的高斯消去,这是在串行计算机上求解密集的、非结构化的n X n线性方程组Ax = b的通用方法。这个算法是如此成功,以至于对我们中的许多人来说,高斯消去法和Ax = b或多或少是同义词。Golub和Van Loan[3]的书中的章节标题是典型的-与“正交化和最小二乘法”,“对称特征值问题”以及其他内容一起,人们发现“高斯消去”,而不是“线性方程组”。
If numerical analysts understand anything, surely it must be Gaussian elimination. This is the oldest and truest of numerical algorithms. To be precise, I am speaking of Gaussian elimination with partial pivoting, the universal method for solving a dense, unstructured n X n linear system of equations Ax = b on a serial computer. This algorithm has been so successful that to many of us, Gaussian elimination and Ax = b are more or less synonymous. The chapter headings in the book by Golub and Van Loan [3] are typical -- along with "Orthogonalization and Least Squares Methods," "The Symetric Eigenvalue Problem," and the rest, one finds "Gaussian Elimination," not "Linear Systems of Equations."