SVDï¼Singular Value Decompositionãç¹ç°å¤å解ï¼ã«ã¤ãã¦è§£èª¬ãã¾ãã SVDã¨ã¯ ã©ã使ãã®ã ã¡ãã£ã¨è¨¼æ SVDã¨ã¯ ããè¡å $A$ ããã£ã¦ãããã A = (\boldsymbol{u}_1, \boldsymbol{u}_2, \cdots, \boldsymbol{u}_n) \begin{pmatrix} \sigma_1 & & & \\ & \sigma_2 & & \\ & & \ddots & \\ & & & \sigma_n \end{pmatrix} \begin{pmatrix} \boldsymbol{v}_1^{\mathrm{T}} \\ \boldsymbol{v}_2^{\mathrm{T}} \\ \vdots \\ \boldsymbol{v}_n^{\mathrm{T}} \end{pmatrix} ã¨ããæ¡ä»¶ã
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