Numerical Linear Algebra

书名：Numerical Linear Algebra
作者：LloydN.Trefethen/DavidBauIII
译者：
ISBN：9780898713619
出版社：SIAM:SocietyforIndustrialandAppliedMathematics
出版时间：1997-06-01
格式：epub/mobi/azw3/pdf
页数：361
豆瓣评分： 9.2

书籍简介：

Numerical Linear Algebra is a concise, insightful, and elegant introduction to the field of numerical linear algebra.

作者简介：

书友短评：

@ newleft Talking much about matrices in the first, but detailed and amplified iterative algorithms are provided later. Nice structure and good exercises in the end (Used by Prof Michael Neilan in his course "Iterative Methods" in third year of my PhD). @ 染污 对于工程师够用了咱又不是数学家 书里偶尔冒出两句俏皮话还挺逗的 @ 洛斯里克外乡人 It's more like a math handbook rather than a textbook, readable, easy to check concepts and love those sudo codes of each algorithm @ 崽崽-旋夜 不愧是numerical linear algebra的圣经，简而易懂，尤其是projection那章，真的给跪了 @ 谁家的鸡 很好的一本书，比著名的 Golub and Van Loan 简洁许多。大部分都写的非常好，唯一的缺点是 sparse matrix 的 iterative 算法讲得太粗糙了。Conjugate gradient 的引入非常糟糕。后者的话还是去翻 Golub 比较好

Preface; Part I. Fundamental: 1. Matrix-vector multiplication; 2. Orthogonal vectors and matrices; 3. Norms; 4. The singular value decomposition; 5. More on the SVD; Part II. QR Factorization and Least Squares: 6. Projectors; 7. QR factorization; 8. Gram-Schmidt orthogonalization; 9. MATLAB; 10. Householder triangularization; 11. Least squares problems; Part III. Conditioning and Stability: 12. Conditioning and condition numbers; 13. Floating point arithmetic; 14. Stability; 15. More on stability; 16. Stability of householder triangularization; 17. Stability of back substitution; 18. Conditioning of least squares problems; 19. Stability of least squares algorithms; Part IV. Systems of Equations: 20. Gaussian elimination; 21. Pivoting; 22. Stability of Gaussian elimination; 23. Cholesky factorization; Part V. Eigenvalues: 24. Eigenvalue problems; 25. Overview of Eigenvalue algorithms; 26. Reduction to Hessenberg or tridiagonal form; 27. Rayleigh quotient, inverse iteration; 28. QR algorithm without shifts; 29. QR algorithm with shifts; 30. Other Eigenvalue algorithms; 31. Computing the SVD; Part VI. Iterative Methods: 32. Overview of iterative methods; 33. The Arnoldi iteration; 34. How Arnoldi locates Eigenvalues; 35. GMRES; 36. The Lanczos iteration; 37. From Lanczos to Gauss quadrature; 38. Conjugate gradients; 39. Biorthogonalization methods; 40. Preconditioning; Appendix; Notes; Bibliography; Index.
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　　Other Titles in Applied Mathematics(共114册)，这套丛书还有《Matrix analysis for scientists and engineers》《Complex Variables and Analytic Functions》《Approximation and Modeling with B-Splines》《A Primer on Mathematical Models in Biology》《Numerical Analysis》等。

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