行列式的向量形式
行列式的向量形式
行列式公式
\[|A| = \begin{vmatrix}
a_{11} & a_{12} & \cdots & a_{1n}\\
a_{21} & a_{22} & \cdots & a_{2n}\\
\vdots & \vdots & \ddots & \vdots\\
a_{n1} & a_{n2} & \cdots & a_{nn}\\
\end{vmatrix}\]
行向量表示
令\(\alpha_i = (a_{i1} , a_{i2} , \cdots , a_{in}), i\in(1,2,\cdots,n)\), 则行列式可以表示为
\[|A| = \begin{vmatrix}
a_{11} & a_{12} & \cdots & a_{1n}\\
a_{21} & a_{22} & \cdots & a_{2n}\\
\vdots & \vdots & \ddots & \vdots\\
a_{n1} & a_{n2} & \cdots & a_{nn}\\
\end{vmatrix} =
\begin{vmatrix} \alpha_1 \\ \alpha_2 \\ \vdots \\ \alpha_n \end{vmatrix}\]
性质2(0向量)
\[|A|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ 0 \\ \vdots \\ \alpha_n \end{vmatrix} =0\]
性质3(某一向量的倍数)
\[|B|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ c\alpha_i \\ \vdots \\ \alpha_n \end{vmatrix} =c\begin{vmatrix} \alpha_1 \\ \vdots \\ \alpha_i \\ \vdots \\ \alpha_n \end{vmatrix} = c|A|\]
性质4(两行互换)
\[|B|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ \alpha_j \\ \vdots \\ \alpha_i \\ \vdots \\ \alpha_n \end{vmatrix} = -\begin{vmatrix} \alpha_1 \\ \vdots \\ \alpha_i \\ \vdots \\ \alpha_j \\ \vdots \\ \alpha_n \end{vmatrix} = -|A|\]
性质5(向量加法c=a+b)
\[|C|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ a+b \\ \vdots \\ \alpha_n \end{vmatrix} =\begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ \alpha_n \end{vmatrix}
+\begin{vmatrix} \alpha_1 \\ \vdots \\ b \\ \vdots \\ \alpha_n \end{vmatrix}
=|A|+|B|\]
性质6(两行成比例)
\[|B|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ ca \\ \vdots \\ \alpha_n \end{vmatrix} = c\begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ a \\ \vdots \\ \alpha_n \end{vmatrix} = 0\]
性质7(倍加)
\[|B|=
\begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ ca+b \\ \vdots \\ \alpha_n \end{vmatrix} = \begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ ca \\ \vdots \\ \alpha_n \end{vmatrix} + \begin{vmatrix} \alpha_1 \\ \vdots \\ a \\ \vdots \\ b \\ \vdots \\ \alpha_n \end{vmatrix} = |A|\]
列向量表示
令\(\beta_i = \begin{pmatrix}a_{1i} \\ a_{2i} \\ \vdots \\ a_{ni}\end{pmatrix}, i\in(1,2,\cdots,n)\), 则行列式可以表示为
\[|A| = \begin{vmatrix}
a_{11} & a_{12} & \cdots & a_{1n}\\
a_{21} & a_{22} & \cdots & a_{2n}\\
\vdots & \vdots & \ddots & \vdots\\
a_{n1} & a_{n2} & \cdots & a_{nn}\\
\end{vmatrix} =
\begin{vmatrix} \beta_1 & \beta_2 & \cdots & \beta_n \end{vmatrix}\]
性质2(0向量)
\[|A|=
\begin{vmatrix} \beta_1 & \cdots & 0 & \cdots & \beta_n \end{vmatrix} =0\]
性质3(某一向量的倍数)
\[|B|=
\begin{vmatrix} \beta_1 & \cdots & c\beta_i & \cdots & \beta_n \end{vmatrix} \]
\[=c\begin{vmatrix} \beta_1 & \cdots & \beta_i & \cdots & \beta_n \end{vmatrix}
\]
\[= c|A|
\]
性质4(两行互换)
\[|B|=
\begin{vmatrix} \beta_1 & \cdots & \beta_j & \cdots & \beta_i & \cdots & \beta_n \end{vmatrix}\]
\[= -\begin{vmatrix} \beta_1 & \cdots & \beta_i & \cdots & \beta_j & \cdots & \beta_n \end{vmatrix}
\]
\[= -|A|
\]
性质5(向量加法c=a+b)
\[|C|=
\begin{vmatrix} \beta_1 & \cdots & a+b & \cdots & \beta_n \end{vmatrix} \]
\[=\begin{vmatrix} \beta_1 & \cdots & a & \cdots & \beta_n \end{vmatrix}
+\begin{vmatrix} \beta_1 & \cdots & b & \cdots & \beta_n \end{vmatrix}
\]
\[=|A|+|B|
\]
性质6(两行成比例)
\[|B|=
\begin{vmatrix} \beta_1 & \cdots & a & \cdots & ca & \cdots & \beta_n \end{vmatrix} \]
\[= c\begin{vmatrix} \beta_1 & \cdots & a & \cdots & a & \cdots & \beta_n \end{vmatrix}
\]
\[= 0
\]
性质7(倍加)
\[|B|=
\begin{vmatrix} \beta_1 & \cdots & a & \cdots & ca+b & \cdots & \beta_n \end{vmatrix} \]
\[= \begin{vmatrix} \beta_1 & \cdots & a & \cdots & ca & \cdots & \beta_n \end{vmatrix} + \begin{vmatrix} \beta_1 & \cdots & a & \cdots & b & \cdots & \beta_n \end{vmatrix}
\]
\[= |A|
\]
