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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Derivation of the conjugate gradient method ： ウィキペディア英語版 Derivation of the conjugate gradient method In numerical linear algebra, the conjugate gradient method is an iterative method for numerically solving the linear system :$\backslash boldsymbol=\backslash boldsymbol$ where $\backslash boldsymbol$ is symmetric positive-definite. The conjugate gradient method can be derived from several different perspectives, including specialization of the conjugate direction method for optimization, and variation of the Arnoldi/Lanczos iteration for eigenvalue problems. The intent of this article is to document the important steps in these derivations. ==Derivation from the conjugate direction method== The conjugate gradient method can be seen as a special case of the conjugate direction method applied to minimization of the quadratic function :$f(\backslash boldsymbol)=\backslash boldsymbol^\backslash mathrm\backslash boldsymbol\backslash boldsymbol-2\backslash boldsymbol^\backslash mathrm\backslash boldsymbol\backslash text$ 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Derivation of the conjugate gradient method」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.