Titlebook: Iterative Solution of Large Sparse Systems of Equations; Wolfgang Hackbusch Book 2016Latest edition Springer International Publishing Swit

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書目名稱Iterative Solution of Large Sparse Systems of Equations影響因子(影響力)




書目名稱Iterative Solution of Large Sparse Systems of Equations影響因子(影響力)學科排名




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書目名稱Iterative Solution of Large Sparse Systems of Equations網(wǎng)絡公開度學科排名




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書目名稱Iterative Solution of Large Sparse Systems of Equations被引頻次學科排名




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書目名稱Iterative Solution of Large Sparse Systems of Equations年度引用學科排名




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書目名稱Iterative Solution of Large Sparse Systems of Equations讀者反饋學科排名

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Gradient Methodection 9.3 we discuss the drawback of the gradient directions and introduce the conjugate directions in preparation for the conjugate gradient method in the next chapter. The final Section 9.4 mentions a variant of the gradient method: the minimal residual iteration which can be applied to any regular matrix ..

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Domain Decomposition and Subspace MethodsHere we distinguish between the additive and multiplicative subspace iteration as explained in the corresponding Sections 12.6 and 12.7. Illustrations follow in Section 12.8. Interestingly, multigrid iterations can also be considered as subspace iterations as analysed in Section 12.9.

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Introductiondirect solution by the Gauss elimination is determined. This cost can be compared with the cost of the iterative methods introduced later. In Section 1.6, the Gauss–Seidel and SOR iteration are presented as first examples of linear iterations. Finally, in Section 1.7, sparsity of the underlying matrix discussed.

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-LU Iterationrrespondingly, the .-LU iteration described in Section 13.4 is very fast. The variant discussed in . 13.4.2 is purely algebraic, i.e., the data needed for the iteration are only based on the underlying matrix. Concerning details about the technique of hierarchical matrices, we refer to Appendix D.