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In this chapter, we extend the methods already discussed for solving \(Ax=b\) . As a reminder, in Chap. 3 and Chap. 4 we studied direct methods (i.e., LU, Cholesky, and QR factorization) and iterative methods (i.e., Richardson, Jacobi, Gauss-Seidel). A motivation for iterative methods is the lower memory requirement and generally lower cost complexity.

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Krylov Subspace Methods

  • 章节

  • 发表日期：

    2026年

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  • Thomas Richter,
  • Henry von Wahl,
  • Thomas Wick

摘要

In this chapter, we extend the methods already discussed for solving \(Ax=b\) . As a reminder, in Chap. 3 and Chap. 4 we studied direct methods (i.e., LU, Cholesky, and QR factorization) and iterative methods (i.e., Richardson, Jacobi, Gauss-Seidel). A motivation for iterative methods is the lower memory requirement and generally lower cost complexity.