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Titlebook: Numerical Analysis and Its Applications; Second International Lubin Vulkov,Plamen Yalamov,Jerzy Wa?niewski Conference proceedings 2001 Spri

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31#
發(fā)表于 2025-3-26 23:02:45 | 只看該作者
On Solving Large-Scale Weighted Least Squares Problemssparse matrix with some dense columns; has many applications in linear programming, electrical networks, elliptic boundary value problems, and structural analysis. We discuss a technique for forming low-rank correction preconditioners for such problems. Finally we give numerical results to illustrat
32#
發(fā)表于 2025-3-27 01:31:25 | 只看該作者
33#
發(fā)表于 2025-3-27 08:25:37 | 只看該作者
Inexact Newton Methods and Mixed Nonlinear Complementary Problemshe linearized systems are solved with two preconditioners particularly suited for parallel computation. We report the results for the solution of some nonlinear problems on the CRAY T3E under the MPI environment. Our methods may be used to solve more general problems. Due to the presence of a logari
34#
發(fā)表于 2025-3-27 10:31:00 | 只看該作者
35#
發(fā)表于 2025-3-27 17:24:56 | 只看該作者
New Families of Symplectic Runge-Kutta-Nystr?m Integration Methodsusly known algorithms. The methods use the processing technique and non-trivial flows associated with different elements of the Lie algebra involved in the problem. Both the processor and the kernel are compositions of explicitly computable maps.
36#
發(fā)表于 2025-3-27 18:56:39 | 只看該作者
Convergence of Finite Difference Method for Parabolic Problem with Variable Operator assume that the solution of the problem and the coefficients of equation belong to the corresponding anisotropic Sobolev spaces. Convergence rate estimates consistent with the smoothness of the data are obtained.
37#
發(fā)表于 2025-3-27 23:32:34 | 只看該作者
38#
發(fā)表于 2025-3-28 03:48:39 | 只看該作者
39#
發(fā)表于 2025-3-28 07:37:07 | 只看該作者
Fractional Step Runge-Kutta Methods for the Resolution of Two Dimensional Time Dependent Coefficient in the numerical resolution of parabolic problems whose coefficients depend on time. These methods combined with standard spatial discretizations will provide totally discrete algorithms with low computational cost and high order of accuracy in time. We will show the efficiency of such methods, in
40#
發(fā)表于 2025-3-28 11:03:49 | 只看該作者
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