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단행본

Matrix computations

판사항
4th ed
발행사항
Baltimore : The Johns Hopkins University Press, [2013]
형태사항
xxi, 756 p. : ill. ; 26 cm
서지주기
Includes bibliographical references and index
소장정보
위치등록번호청구기호 / 출력상태반납예정일
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자료실E205554대출가능-
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책 소개

A comprehensive treatment of numerical linear algebra from the standpoint of both theory and practice.

The fourth edition of Gene H. Golub and Charles F. Van Loan's classic is an essential reference for computational scientists and engineers in addition to researchers in the numerical linear algebra community. Anyone whose work requires the solution to a matrix problem and an appreciation of its mathematical properties will find this book to be an indispensible tool.

This revision is a cover-to-cover expansion and renovation of the third edition. It now includes an introduction to tensor computations and brand new sections on
? fast transforms
? parallel LU
? discrete Poisson solvers
? pseudospectra
? structured linear equation problems
? structured eigenvalue problems
? large-scale SVD methods
? polynomial eigenvalue problems

Matrix Computations is packed with challenging problems, insightful derivations, and pointers to the literature?everything needed to become a matrix-savvy developer of numerical methods and software. The second most cited math book of 2012 according to MathSciNet, the book has placed in the top 10 for since 2005.



Reviews

A mine of insight and information and a provocation to thought; the annotated bibliographies are helpful to those wishing to explore further. One could not ask for more, and the book should be considered a resounding success.
?Bulletin of the Institute of Mathematics and Its Applications

목차
Preface Global References Other Books Useful URLs Common Notation 1. Matrix multiplication 2. Matrix analysis 3. General linear systems 4. Special linear systems 5. Orthogonalization and least squares 6. Modified least squares problems and methods 7. Unsymmetric eigenvalue problems 8. Symmetric eigenvalue problems 9. Functions of matrices 10. Large sparse eigenvalue problems 11. Large sparse linear system problems 12. Special topics Index