| 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 |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 512.5 T786n | 등록번호 121149669 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. 2 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 512.5 T786n | 등록번호 121238093 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
목차
- 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.
정보제공 :
