奇異值分解 (SVD)

现代启示录

線代啟示錄

本文的閱讀等級:中級

奇異值分解 (singular value decomposition,以下簡稱 SVD) 被譽為矩陣分解的「瑞士刀」和「勞斯萊斯」[1],前者說明它的用途非常廣泛,後者意味它是值得珍藏的精品。在“線性代數基本定理 (四)”一文,我們介紹了 SVD 的推導,並於矩陣的四個子空間分析平台解釋其幾何涵義,本文簡述 SVD 重點並舉一例說明分解式的計算步驟。

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