MIT18.06 Linear Algebra (1-3)

矩阵乘法的性质

顺序不能改变,可以任意添加括号

(AB)C=A(BC)(AB)C=A(BC)

矩阵乘法的定义

从单个元素

Cij=kAikBkjC_{ij}=\sum_{k}A_{ik}B_{kj}

从列

Clip_20220306_122632.png

A * col 1 of B = col 1 of C
cols of B 对 cols of A的线性组合

从行

row 1 of A * B = row 1 of C

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列x行

[ ab cd][ efg hij]=[ a c][ efg]+[ b d][ hij]=C\begin{bmatrix}  a&b \\  c&d\end{bmatrix}\begin{bmatrix}  e & f & g \\  h & i & j\end{bmatrix} =\begin{bmatrix}  a \\  c\end{bmatrix}\begin{bmatrix}  e & f & g\end{bmatrix}+\begin{bmatrix}  b \\  d\end{bmatrix}\begin{bmatrix}  h & i & j\end{bmatrix}=C

矩阵代替元素

[    A1A2   A3A4   ][    B1B2   B3B4   ]=[    C1C2   C3C4   ]C1=A1B1+A2B3\begin{bmatrix}   \begin{array}{c | c}   A_1 & A_2 \\ \hline    A_3 & A_4   \end{array} \end{bmatrix}\begin{bmatrix}   \begin{array}{c | c}   B_1 & B_2 \\ \hline    B_3 & B_4   \end{array} \end{bmatrix}=\begin{bmatrix}   \begin{array}{c | c}   C_1 & C_2 \\ \hline    C_3 & C_4   \end{array} \end{bmatrix} \\C_1=A_1B_1+A_2B_3

矩阵的逆(方阵)

性质

A1A=I(单位矩阵)AA1=IA^{-1}A=I\text{(单位矩阵)}\\AA^{-1}=I

即 左逆=右逆 (方阵)

矩阵的逆存在时,称矩阵为可逆(invertible)或 非奇异的(non-singular)

不可逆的矩阵:

e.g.

A=[ 13 26]A=\begin{bmatrix}  1 & 3 \\  2 & 6\end{bmatrix}

$\begin{bmatrix}  1 & 3 \end{bmatrix} \begin{bmatrix} 2 & 6\end{bmatrix} 共线,所以共线,所以 \begin{bmatrix}  1 & 3 \end{bmatrix} \begin{bmatrix} 2 & 6\end{bmatrix} 的线性组合无法得到的线性组合无法得到 \begin{bmatrix} 1 & 0\end{bmatrix} \begin{bmatrix} 0 & 1 \end{bmatrix}$

proof.  ifA1:(A1A)x=Ix=xA1(Ax)=A10=0x=0proof.\;if \exists A^{-1}: \\(A^{-1}A)x=Ix=x \\A^{-1}(Ax)=A^{-1}0=0 \\ \Rightarrow x=0

求解逆矩阵:Gauss- Jordan消元法

e.g.

A=[1327],A1=?A=\begin{bmatrix} 1 & 3\\ 2 & 7\end{bmatrix} , A^{-1} = ?

[13102701]A      I[13010121][10730121]I        A1\begin{align} &\begin{array}{c} \begin{bmatrix} \begin{array}{cc|cc}1 & 3 & 1 & 0 \\2 & 7 & 0 & 1\end{array}\end{bmatrix} \\A\;\;\;I\end{array}\\\to &\begin{array}{c} \begin{bmatrix} \begin{array}{cc|cc}1 & 3 & 0 & 1 \\0 & 1 & -2 & 1\end{array}\end{bmatrix}\end{array} \\\to &\begin{array}{c} \begin{bmatrix} \begin{array}{cc|cc}1 & 0 & 7 & -3 \\0 & 1 & -2 & 1\end{array}\end{bmatrix}\\I \;\;\;\;A^{-1}\end{array}\end{align}

A1=[ 73 21]A^{-1} = \begin{bmatrix} 7 & -3\\ -2 & 1\end{bmatrix}

proof.EA=IE=A1IE=E=A1proof. \\ EA=I\Rightarrow E=A^{-1} \\ IE=E=A^{-1}

一般Gauss消元

[11212381120412][121202260412][1212022600510]主元(pivot)上三角(upper triangle)矩阵\begin{align} &\begin{bmatrix} \begin{array}{ccc|c} 1 & 12& 1 & 2 \\ 3 & 8 & 1 & 12 \\ 0 & 4 & 1 & 2 \end{array} \end{bmatrix} \\ \to & \begin{bmatrix} \begin{array}{ccc|c} 1 & 2 & 1 & 2 \\ 0 & 2 & -2 & 6 \\ 0 & 4 & -1 & 2 \end{array} \end{bmatrix} \\ \to & \begin{array}{c} \begin{bmatrix} \begin{array}{ccc|c} \color{red}{1} & 2 & 1 & 2 \\ 0 & \color{red}{2} & -2 & 6 \\ 0 & 0 & \color{red}{5} & -10 \end{array} \end{bmatrix} \\ \color{red}{\text{主元(pivot)}} \\ \text{上三角(upper triangle)矩阵} \end{array} \end{align}

进行的初等变换等价于左乘一个消元矩阵 EE .

e.g.

E=[ 100 310 001]E=\begin{bmatrix} 1 & 0 & 0\\ -3 & 1 & 0\\ 0 & 0 & 1\end{bmatrix}

$EA :substract3row1of: substract 3 * row 1 of A fromrow2offrom row 2 of A$.


MIT18.06 Linear Algebra (1-3)
https://yzzzf.xyz/2022/09/13/MIT16.08-lec1-3/
Author
Zifan Ying
Posted on
September 13, 2022
Licensed under