淹没 发表于 2025-3-21 18:09:19
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Solving Systems of Linear Equations,e number of steps, whereas classical iterative methods aim at converging towards the solution in an infinite number of steps. Krylov subspace iteration has blurred the lines, as it would converge to the exact solution in a finite number of steps if the computations were carried out exactly, just as direct methods.Maximizer 发表于 2025-3-22 16:42:09
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Optimizing Under Constraints,e most spectacular achievements of the interior-point approach has been to show how linear programming could be carried out with algorithms for convex optimization that have a much smaller worst-case complexity than Dantzig’s simplex.pineal-gland 发表于 2025-3-22 22:14:59
Solving Ordinary Differential Equations,lue problems (BVPs) are finally considered, and in particular two-endpoint BVPs, where partial information is available on the initial and final states. Since most methods for solving BVPs for ODEs extend to solving partial differential equations, this latter part also serves as an introduction to the next chapter.懦夫 发表于 2025-3-23 03:45:30
Interpolating and Extrapolating,ce, in numerical integration and differentiation as well as for solving differential equations. Kriging, a multivariate interpolation method initially developed in the context of mining, receives special attention. It is increasingly used in computer experiments to build surrogate models for functions that are very costly to evaluate.Nefarious 发表于 2025-3-23 09:16:44
Solving Partial Differential Equations,ar PDEs are important enough to receive a classification of their own, which is recalled. The basic principles, advantages, and drawbacks of finite-difference and finite-element methods are explained, and their understanding is facilitated by the fact that the same methods have been applied to ODEs in the previous chapter.