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Numerical linear algebra

Numerical linear algebra (Loan 26 times)

Material type
단행본
Personal Author
Trefethen, Lloyd N. (Lloyd Nicholas). Bau, David.
Title Statement
Numerical linear algebra / Lloyd N. Trefethen, David Bau.
Publication, Distribution, etc
Philadelphia :   Society for Industrial and Applied Mathematics,   1997.  
Physical Medium
xii, 361 p. : ill. ; 26 cm.
ISBN
0898713617 (alk. paper) 9780898713619
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Algebras, Linear. Numerical calculations.
000 00000cam u2200205 a 4500
001 000045368079
005 20161103112422
008 961210s1997 paua b 001 0 eng
010 ▼a 96052458
020 ▼a 0898713617 (alk. paper)
020 ▼a 9780898713619
035 ▼a (KERIS)REF000006380962
040 ▼a DLC ▼c DLC ▼d DLC ▼d 211009
050 0 0 ▼a QA184 ▼b .T74 1997
082 0 0 ▼a 512/.5 ▼2 23
084 ▼a 512.5 ▼2 DDCK
090 ▼a 512.5 ▼b T786n
100 1 ▼a Trefethen, Lloyd N. ▼q (Lloyd Nicholas).
245 1 0 ▼a Numerical linear algebra / ▼c Lloyd N. Trefethen, David Bau.
260 ▼a Philadelphia : ▼b Society for Industrial and Applied Mathematics, ▼c 1997.
300 ▼a xii, 361 p. : ▼b ill. ; ▼c 26 cm.
504 ▼a Includes bibliographical references and index.
650 0 ▼a Algebras, Linear.
650 0 ▼a Numerical calculations.
700 1 ▼a Bau, David.
945 ▼a KINS

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 512.5 T786n Accession No. 121149669 Availability Available Due Date Make a Reservation Service B M
No. 2 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 512.5 T786n Accession No. 121238093 Availability Available Due Date Make a Reservation Service B M

Contents information

Table of Contents

  • Preface
  • Acknowledgments
  • Part I: Fundamentals. Lecture 1: Matrix-Vector Multiplication
  • Lecture 2: Orthogonal Vectors and Matrices
  • Lecture 3: Norms
  • Lecture 4: The Singular Value Decomposition
  • Lecture 5: More on the SVD
  • Part II: QR Factorization and Least Squares. Lecture 6: Projectors
  • Lecture 7: QR Factorization
  • Lecture 8: Gram-Schmidt Orthogonalization
  • Lecture 9: MATLAB
  • Lecture 10: Householder Triangularization
  • Lecture 11: Least Squares Problems
  • Part III: Conditioning and Stability. Lecture 12: Conditioning and Condition Numbers
  • Lecture 13: Floating Point Arithmetic
  • Lecture 14: Stability
  • Lecture 15: More on Stability
  • Lecture 16: Stability of Householder Triangularization
  • Lecture 17: Stability of Back Substitution
  • Lecture 18: Conditioning of Least Squares Problems
  • Lecture 19: Stability of Least Squares Algorithms
  • Part IV: Systems of Equations. Lecture 20: Gaussian Elimination
  • Lecture 21: Pivoting
  • Lecture 22: Stability of Gaussian Elimination
  • Lecture 23: Cholesky Factorization
  • Part V: Eigenvalues. Lecture 24: Eigenvalue Problems
  • Lecture 25: Overview of Eigenvalue Algorithms
  • Lecture 26: Reduction to Hessenberg or Tridiagonal Form
  • Lecture 27: Rayleigh Quotient, Inverse Iteration
  • Lecture 28: QR Algorithm without Shifts
  • Lecture 29: QR Algorithm with Shifts
  • Lecture 30: Other Eigenvalue Algorithms
  • Lecture 31: Computing the SVD
  • Part VI: Iterative Methods. Lecture 32: Overview of Iterative Methods
  • Lecture 33: The Arnoldi Iteration
  • Lecture 34: How Arnoldi Locates Eigenvalues
  • Lecture 35: GMRES
  • Lecture 36: The Lanczos Iteration
  • Lecture 37: From Lanczos to Gauss Quadrature
  • Lecture 38: Conjugate Gradients
  • Lecture 39: Biorthogonalization Methods
  • Lecture 40: Preconditioning
  • Appendix: The Definition of Numerical Analysis
  • Notes
  • Bibliography
  • Index.

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