图书简介
Preface; Part I. Preliminaries: Mathematical Modeling, Errors, Hardware, and Software; 1. Errors and arithmetic; 2. Sensitivity analysis: when a little means a lot; 3. Computer memory and arithmetic: a look under the hood; 4. Design of computer programs: writing your legacy; Part II. Dense Matrix Computations: 5. Matrix factorizations; 6. Case study: image deblurring: I can see clearly now; 7. Case study: updating and downdating matrix factorizations: a change in plans; 8. Case study: the direction-of-arrival problem; Part III. Optimization and Data Fitting: 9. Numerical methods for unconstrained optimization; 10. Numerical methods for constrained optimization; 11. Case study: classified information: the data clustering problem; 12. Case study: achieving a common viewpoint: yaw, pitch, and roll; 13. Case study: fitting exponentials: an interest in rates; 14. Case study: blind deconvolution: errors, errors, everywhere; 15. Case study: blind deconvolution: a matter of norm; Part IV. Monte Carlo Computations: 16. Monte Carlo principles; 17. Case study: Monte-Carlo minimization and counting one, two, too many; 18. Case study: multidimensional integration: partition and conquer; 19. Case study: models of infections: person to person; Part V. Ordinary Differential Equations: 20. Solution of ordinary differential equations; 21. Case study: more models of infection: it’s epidemic; 22. Case study: robot control: swinging like a pendulum; 23. Case study: finite differences and finite elements: getting to know you; Part VI. Nonlinear Equations and Continuation Methods: 24. Nonlinear systems; 25. Case study: variable-geometry trusses; 26. Case study: beetles, cannibalism, and chaos; Part VII. Sparse Matrix Computations with Application to Partial Differential Equations: 27. Solving sparse linear systems: taking the direct approach; 28. Iterative methods for linear systems; 29. Case study: elastoplastic torsion: twist and stress; 30. Case study: fast solvers and Sylvester equations: both sides now; 31. Case study: eigenvalues: valuable principles; 32. Multigrid methods: managing massive meshes; Bibliography; Index.
馆藏图书馆
Yale University Library
computational mathematics, numerical analysis, education, math and computation in industry
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