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ベクトルと行列の微分

定義と表記

ベクトルと行列の表記

\(\boldsymbol{x}=\begin{pmatrix}x_1 \\ x_2 \\ \vdots \\ x_n \end{pmatrix}\)

\(\boldsymbol{A}=\begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots & \vdots & \ddots & \vdots \\ a_{n1} & a_{n2} & \cdots & a_{nm} \end{pmatrix}\)

転置記号

\(\boldsymbol{x}^T=(x_1,x_2,\cdots,x_n) \)

\(\boldsymbol{A}^T=\begin{pmatrix} a_{11} & a_{21} & \cdots & a_{n1} \\ a_{12} & a_{22} & \cdots & a_{n1} \\ \vdots & \vdots & \ddots & \vdots \\ a_{1n} & a_{2n} & \cdots & a_{mn} \end{pmatrix}\)

演算

行列の積

\[ \boldsymbol{A}=\begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1m} \\ a_{21} & a_{22} & \cdots & a_{2m} \\ \vdots & \vdots & \ddots & \vdots \\ a_{n1} & a_{n2} & \cdots & a_{nm} \end{pmatrix} \ \] \[ \boldsymbol{B}=\begin{pmatrix} b_{11} & b_{12} & \cdots & b_{1l} \\ b_{21} & b_{22} & \cdots & b_{2l} \\ \vdots & \vdots & \ddots & \vdots \\ b_{m1} & b_{m2} & \cdots & b_{ml} \end{pmatrix} \] と\(n \times m\)行列と\(m \times l\)行列を用意する.
行列の積を \[ \boldsymbol{A}\boldsymbol{B}=\begin{pmatrix} \sum^m_{i=1} a_{1i}b_{i1} & \sum^m_{i=1} a_{1i}b_{i2} & \sum^m_{i=1} a_{1i}b_{i3} & \cdots & \sum^m_{i=1} a_{1i}b_{il} \\ \sum^m_{i=1} a_{2i}b_{i1} & \sum^m_{i=1} a_{2i}b_{i2} & \sum^m_{i=1} a_{2i}b_{i3} & \cdots & \sum^m_{i=1} a_{2i}b_{il} \\ \vdots & \vdots & \ddots & \vdots \\ \sum^m_{i=1} a_{ni}b_{i1} & \sum^m_{i=1} a_{ni}b_{i2} & \sum^m_{i=1} a_{ni}b_{i3} & \cdots & \sum^m_{i=1} a_{ni}b_{il} \end{pmatrix} \ \] と定義する. 可換性は無い. 被乗数側の列数と乗数側の行数が一致しないと行けない.

ベクトルの内積と外積

内積

\(\boldsymbol{x}^T=(x_1,x_2,\cdots,x_n) \) \(\boldsymbol{y}^T=(y_1,y_2,\cdots,y_n) \) とn列ベクトルを用意する.
ベクトルの内積(ドット積)は以下のように定義する.
\[ \boldsymbol{x} \cdot \boldsymbol{y}\ = x_1y_1 + x_2y_2 + \cdots + x_ny_n \] 縦ベクトルを\(1 \times n\)の横ベクトルを\(n \times 1\)の行列と見なすと, \[ \boldsymbol{x} \cdot \boldsymbol{y}\ = \boldsymbol{x}^T\boldsymbol{y} = \boldsymbol{y}^T\boldsymbol{x} \] と表せる.

外積

\(\boldsymbol{x}^T=(x_1,x_2,\cdots,x_n) \) \(\boldsymbol{y}^T=(y_1,y_2,\cdots,y_m) \) \(\boldsymbol{x}\boldsymbol{y}^T\)としたとき,それぞれを\(n \times 1\)行列,\(1 \times m\)行列とみなすと,演算の結果は,\(n \times m\)行列となるのが自然である. \[ \boldsymbol{x}\boldsymbol{y}^T = \begin{pmatrix} x_{1}y_{1} & x_{1}y_{2} & x_{1}y_{3} & \cdots & x_{1}y_{m} \\ x_{2}y_{1} & x_{2}y_{2} & x_{2}y_{3} & \cdots & x_{2}y_{m} \\ \vdots & \vdots & \vdots & \ddots & \vdots \\ x_{n}y_{1} & x_{n}y_{2} & x_{n}y_{3} & \cdots & x_{n}y_{m} \\ \end{pmatrix} \] として外積と言う.

転置に関する公式

\[ \begin{align} \boldsymbol{x}^T \boldsymbol{A} &= \begin{pmatrix} x_{1} & x_{2} & \cdots & x_{n} \end{pmatrix} \begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1m} \\ a_{21} & a_{22} & \cdots & a_{2m} \\ \vdots & \vdots & \ddots & \vdots \\ a_{n1} & a_{n2} & \cdots & a_{nm} \\ \end{pmatrix} \\ &= \begin{pmatrix} a_{11}x_{1} + a_{21}x_{2} + \cdots + a_{n1}x_{n} & a_{12}x_{1} + a_{22}x_{2} + \cdots + a_{n2}x_{n} & \cdots & a_{1m}x_{1} + a_{2m}x_{2} + \cdots + a_{nm}x_{n} \end{pmatrix} \\ &= \begin{pmatrix} a_{11} & a_{21} & \cdots & a_{n1} \\ a_{12} & a_{22} & \cdots & a_{n2} \\ \vdots & \vdots & \ddots & \vdots \\ a_{1m} & a_{2m} & \cdots & a_{nm} \\ \end{pmatrix} \begin{pmatrix} x_1 \\ x_2 \\ \vdots \\ x_n \end{pmatrix} \\ &= \boldsymbol{A}^T \boldsymbol{x} \end{align} \]

微分演算

微分演算子を以下のように定義する. \[ \frac{\partial}{\partial\boldsymbol{x}}=\begin{pmatrix} \frac{\partial}{\partial x_1} \\ \frac{\partial}{\partial x_2} \\ \vdots \\ \frac{\partial}{\partial x_n} \end{pmatrix}\]

演算定義

\[ \boldsymbol{f}(\boldsymbol{x}) = \begin{pmatrix} f_1(\boldsymbol{x}) & f_2(\boldsymbol{x}) & \cdots & f_m(\boldsymbol{x}) \end{pmatrix} \] として, \[ \frac{\partial \boldsymbol{f}(\boldsymbol{x})}{\partial\boldsymbol{x}} = \begin{pmatrix} \frac{\partial f_1(\boldsymbol{x}) }{\partial x_1} & \frac{\partial f_1(\boldsymbol{x}) }{\partial x_2} & \cdots & \frac{\partial f_1(\boldsymbol{x}) }{\partial x_n} \\ \frac{\partial f_2(\boldsymbol{x}) }{\partial x_1} & \frac{\partial f_2(\boldsymbol{x}) }{\partial x_2} & \cdots & \frac{\partial f_2(\boldsymbol{x}) }{\partial x_n} \\ \vdots & \vdots & \ddots & \vdots \\ \frac{\partial f_m(\boldsymbol{x}) }{\partial x_1} & \frac{\partial f_m(\boldsymbol{x}) }{\partial x_2} & \cdots & \frac{\partial f_m(\boldsymbol{x}) }{\partial x_n} \end{pmatrix} \]

公式

\[ \frac{\partial \boldsymbol{x}}{\partial\boldsymbol{x}} = \begin{pmatrix} 1 & 0 & \cdots & 0 \\ 0 & 1 & \cdots & 0 \\ 0 & 0 & \ddots & 0 \\ 0 & 0 & \cdots & 1 \end{pmatrix} = \boldsymbol{I} \]

\[ \begin{align} \frac{\partial \boldsymbol{A} \boldsymbol{x}}{\partial\boldsymbol{x}} &= \begin{pmatrix} \frac{\partial}{\partial x_1} \\ \frac{\partial}{\partial x_2} \\ \vdots \\ \frac{\partial}{\partial x_n} \end{pmatrix} \begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots & \vdots & \ddots & \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} \end{pmatrix} \begin{pmatrix}x_1 \\ x_2 \\ \vdots \\ x_n \end{pmatrix} \\ &= \begin{pmatrix} \frac{\partial}{\partial x_1} \\ \frac{\partial}{\partial x_2} \\ \vdots \\ \frac{\partial}{\partial x_n} \end{pmatrix} \begin{pmatrix} a_{11}x_1 + a_{12}x_2 + \cdots + a_{1n}x_n \\ a_{21}x_1 + a_{22}x_2 + \cdots + a_{2n}x_n \\ \vdots \\ a_{m1}x_1 + a_{m2}x_2 + \cdots + a_{mn}x_n \end{pmatrix} \\ &= \begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} \end{pmatrix} = \boldsymbol{A} \end{align} \] \[ \begin{align} \frac{\partial \boldsymbol{x}^T \boldsymbol{A} }{\partial\boldsymbol{x}} &= \frac{\partial}{\partial \boldsymbol{x}} \begin{pmatrix} a_{11}x_1 + a_{12}x_2 + \cdots + a_{1n}x_n \\ a_{21}x_1 + a_{22}x_2 + \cdots + a_{2n}x_n \\ \vdots \\ a_{m1}x_1 + a_{m2}x_2 + \cdots + a_{mn}x_n \end{pmatrix} \\ &= \begin{pmatrix} a_{11} & a_{12} & \cdots & a_{1n} \\ a_{21} & a_{22} & \cdots & a_{2n} \\ \vdots \\ a_{m1} & a_{m2} & \cdots & a_{mn} \end{pmatrix} = \boldsymbol{A} \end{align} \] \[ \begin{align} \frac{\partial \boldsymbol{x}^T \boldsymbol{A} \boldsymbol{x} }{\partial\boldsymbol{x}} &= \boldsymbol{A} \boldsymbol{x} + \boldsymbol{x}^T \boldsymbol{A} \\ &= \boldsymbol{A} \boldsymbol{x} + \boldsymbol{A}^T \boldsymbol{x} \\ &= (\boldsymbol{A} + \boldsymbol{A}^T) \boldsymbol{x} \end{align} \]