COMPUTING THE EIGENVECTORS OF A MATRIX WITH MULTIPLEX EIGENVALUES BY SVD METHOD  

作　　者：迟彬 叶庆凯 

机构地区：[1]Department of Mechanics and Engineering Science,Peking University

出　　处：《Applied Mathematics and Mechanics(English Edition)》2004年第3期257-262,共6页应用数学和力学（英文版）

基　　金：theNationalNaturalScienceFoundationofChina ( 699740 0 3 ) ;DoctoralPointFoundationofEducationMinistyPRC ( 2 0 0 1 0 0 0 1 0 1 1 )

摘　　要：Every matrix is similar to a matrix in Jordan canonical form,which has very important sense in the theory of linear algebra and its engineering application.For a matrix with multiplex eigenvalues,an algorithm based on the singular value decomposition(SVD) for computing its eigenvectors and Jordan canonical form was proposed.Numerical simulation shows that this algorithm has good effect in computing the eigenvectors and its Jordan canonical form of a matrix with multiplex eigenvalues.It is superior to MATLAB and MATHEMATICA.Every matrix is similar to a matrix in Jordan canonical form,which has very important sense in the theory of linear algebra and its engineering application.For a matrix with multiplex eigenvalues,an algorithm based on the singular value decomposition(SVD) for computing its eigenvectors and Jordan canonical form was proposed.Numerical simulation shows that this algorithm has good effect in computing the eigenvectors and its Jordan canonical form of a matrix with multiplex eigenvalues.It is superior to MATLAB and MATHEMATICA.

关 键 词：multiplex eigenvalue EIGENVECTOR eigenvector chain Jordan canonical form 

分 类 号：O151.21[理学—数学]