線性代數複習(3)------矩陣乘法與逆

矩陣乘法

前提

兩個矩陣相乘AB=C,A的列數要等於B的行數,否則無法相乘。

行列相乘

首先是最直接的行列相乘:
[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nm} \\\end{bmatrix}[b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\\end{bmatrix}=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\begin{bmatrix}c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{nh} \\\end{bmatrix}

生成的項中cij=l=1mailbljc_{ij}=\sum_{l=1}^ma_{il}b_{lj}
即左邊的一行乘右邊的一列生成矩陣的一個元素。
由此也可以直接的看出AB與BA是不同的。
在看看前後維度的變化:A是nm,B是mh,生成的C是n*h。

列相乘

[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nm} \\\end{bmatrix}[b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\\end{bmatrix}=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\begin{bmatrix}c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{nh} \\\end{bmatrix}
還是原來的運算,但是我們使用列的線性組合來理解。
[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nm} \\\end{bmatrix}[b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\left[ \begin{array} {c| c | c | c | c} b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\ \end{array} \right]=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\left[ \begin{array} {c| c | c | c | c} c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{ nh} \\ \end{array} \right]
細分到每一列就是:
[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nm} \\\end{bmatrix}[b1j...bij...bmj]=\begin{bmatrix}b_{1j} \\... \\b_{ij} \\... \\b_{mj} \\\end{bmatrix}=[c1j...cij...cnj]\begin{bmatrix}c_{1j} \\... \\c_{ij} \\... \\c_{nj} \\\end{bmatrix}
即列之間的線性組合:
[a11...ai1...an1]b1j+...+\begin{bmatrix}a_{11} \\... \\a_{i1} \\... \\a_{n1} \\\end{bmatrix}*b_{1j}+...+[a1j...aij...anj]bij+...+\begin{bmatrix}a_{1j} \\... \\a_{ij} \\... \\a_{nj} \\\end{bmatrix}*b_{ij}+...+[a11...ai1...an1]bmj=\begin{bmatrix}a_{11} \\... \\a_{i1} \\... \\a_{n1} \\\end{bmatrix}*b_{mj}=[c1j...cij...cnj]\begin{bmatrix}c_{1j} \\... \\c_{ij} \\... \\c_{nj} \\\end{bmatrix}

行相乘

[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nm} \\\end{bmatrix}[b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\\end{bmatrix}=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\begin{bmatrix}c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{nh} \\\end{bmatrix}
同樣的方法處理:
[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\left[ \begin{array} {c c c c c} a_{11} & ... & a_{1j} & ...& a_{1m} \\ \hline... & ... & ... & ...& ... \\ \hline a_{i1} &... & a_{ij} & ...& a_{im} \\\hline ... & ... &... & ...& ... \\\hline a_{n1} & ... & a_{nj} & ...& a_{nm} \\ \end{array} \right][b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\\end{bmatrix}=
[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\left[ \begin{array} {c c c c c} c_{11} & ... & c_{1j} & ...& c_{1h} \\\hline ... & ... & ... & ...& ... \\\hline c_{i1} &... & c_{ij} & ...& c_{ih} \\\hline ... & ... &... & ...& ... \\\hline c_{n1} & ... & c_{nj} & ...& c_{ nh} \\ \end{array} \right]
細分到每一行就是B中行之間的線性組合:
[ai1...aij...aim]\begin{bmatrix}a_{i1} &... &a_{ij} &... &a_{im} \\\end{bmatrix}[b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{m1} & ... & b_{mj} & ...& b_{mh} \\\end{bmatrix}=[ci1...cij...cim]\begin{bmatrix}c_{i1} &... &c_{ij} &... &c_{im} \\\end{bmatrix}
展開後有:
ai1[b11...b1j...b1h]+...+a_{i1}*\begin{bmatrix}b_{11} &... &b_{1j} &... &b_{1h} \\\end{bmatrix}+...+aij[bi1...bij...bih]+...+a_{ij}*\begin{bmatrix}b_{i1} &... &b_{ij} &... &b_{ih} \\\end{bmatrix}+...+aim[bm1...bmj...bmh]=a_{im}*\begin{bmatrix}b_{m1} &... &b_{mj} &... &b_{mh} \\\end{bmatrix}=[ci1...cij...cim]\begin{bmatrix}c_{i1} &... &c_{ij} &... &c_{im} \\\end{bmatrix}

列行相乘

這種方式並不那麼直觀,但在之前的基礎上應該可以很好理解:
[a11...a1j...a1m...............ai1...aij...aim...............an1...anj...anm]\left[ \begin{array} {c| c | c | c | c} a_{11} & ... & a_{1j} & ...& a_{1m} \\... & ... & ... & ...& ... \\a_{i1} &... &a_{ij} & ...& a_{im} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{ nm} \\ \end{array} \right][b11...b1j...b1h...............bi1...bij...bih...............bm1...bmj...bmh]=\left[ \begin{array} {c c c c c} b_{11} & ... & b_{1j} & ...& b_{1h} \\\hline ... & ... & ... & ...& ... \\\hline b_{i1} &... & b_{ij} & ...& b_{ih} \\\hline ... & ... &... & ...& ... \\\hline b_{m1} & ... & b_{mj} & ...& b_{ mh} \\ \end{array} \right]=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\begin{bmatrix}c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{nh} \\\end{bmatrix}

將列與行單獨的拆開後有:
[a1j...aij...anj]\begin{bmatrix}a_{1j} \\... \\a_{ij} \\... \\a_{nj} \\\end{bmatrix}[bi1...bij...bih]=\begin{bmatrix}b_{i1} &... &b_{ij} &... &b_{ih} \\\end{bmatrix}=[c^11...c^1j...c^1h...............c^i1...c^ij...c^ih...............c^n1...c^nj...c^nh]\begin{bmatrix} \hat c_{11} & ... & \hat c_{1j} & ...& \hat c_{1h} \\... & ... & ... & ...& ... \\\hat c_{i1} &... & \hat c_{ij} & ...& \hat c_{ih} \\... & ... &... & ...& ... \\\hat c_{n1} & ... & \hat c_{nj} & ...& \hat c_{nh} \\\end{bmatrix}

這裏有一個性質是對於得到的矩陣[c^11...c^1j...c^1h...............c^i1...c^ij...c^ih...............c^n1...c^nj...c^nh]\begin{bmatrix} \hat c_{11} & ... & \hat c_{1j} & ...& \hat c_{1h} \\... & ... & ... & ...& ... \\\hat c_{i1} &... & \hat c_{ij} & ...& \hat c_{ih} \\... & ... &... & ...& ... \\\hat c_{n1} & ... & \hat c_{nj} & ...& \hat c_{nh} \\\end{bmatrix}所有的行向量都相互平行所有的列向量也都相互平行
合併之後有:
l=1m\sum_{l=1}^m[a1l...ail...anl]\begin{bmatrix}a_{1l} \\... \\a_{il} \\... \\a_{nl} \\\end{bmatrix}[bl1...blj...blh]=\begin{bmatrix}b_{l1} &... &b_{lj} &... &b_{lh} \\\end{bmatrix}=[c11...c1j...c1h...............ci1...cij...cih...............cn1...cnj...cnh]\begin{bmatrix}c_{11} & ... & c_{1j} & ...& c_{1h} \\... & ... & ... & ...& ... \\c_{i1} &... & c_{ij} & ...& c_{ih} \\... & ... &... & ...& ... \\c_{n1} & ... & c_{nj} & ...& c_{nh} \\\end{bmatrix}

cij=l=1mailbljc_{ij}=\sum_{l=1}^ma_{il}*b_{lj}與行列相乘相符。

[a11...a1j...a1h...............ai1...aij...aih...............an1...anj...anh]+\begin{bmatrix}a_{11} & ... & a_{1j} & ...& a_{1h} \\... & ... & ... & ...& ... \\a_{i1} &... & a_{ij} & ...& a_{ih} \\... & ... &... & ...& ... \\a_{n1} & ... & a_{nj} & ...& a_{nh} \\\end{bmatrix}+[b11...b1j...b1h...............bi1...bij...bih...............bn1...bnj...bnh]=\begin{bmatrix}b_{11} & ... & b_{1j} & ...& b_{1h} \\... & ... & ... & ...& ... \\b_{i1} &... & b_{ij} & ...& b_{ih} \\... & ... &... & ...& ... \\b_{n1} & ... & b_{nj} & ...& b_{nh} \\\end{bmatrix}=[a11+b11...a1j+b1j...a1h+b1h...............ai1+bi1...aij+bij...aih+bih...............an1+bn1...anj+bnj...ann+bnh]\begin{bmatrix}a_{11}+b_{11} & ... & a_{1j}+b_{1j} & ...& a_{1h}+b_{1h} \\... & ... & ... & ...& ... \\a_{i1}+b_{i1} &... & a_{ij}+b_{ij} & ...& a_{ih}+b_{ih} \\... & ... &... & ...& ... \\a_{n1}+b_{n1} & ... & a_{nj}+b_{nj} & ...& a_{nn}+b_{nh} \\\end{bmatrix}(矩陣相加)

分塊運算

對於一些大的矩陣也可以進行矩陣的劃分,化成幾塊來進行運算,但是劃分之後的矩陣塊也要符合乘法運算的條件(即塊狀的矩陣左邊的列數等於右邊的行數)。
[A11A12A21A22][B11B12B21B22]=[A11B11+A12B21A11B12+A12B22A21B11+A22B21A21B12+A22B22]\left[ \begin{array} {c | c} A_{11} & A_{12} \\\hline A_{21} & A_{22} \\ \end{array} \right]\left[ \begin{array} {c | c} B_{11} & B_{12} \\\hline B_{21} & B_{22} \\ \end{array} \right]=\left[ \begin{array} {c | c} A_{11} B_{11}+A_{12} B_{21} & A_{11} B_{12}+A_{12} B_{22} \\\hline A_{21} B_{11}+A_{22} B_{21} & A_{21} B_{12}+A_{22} B_{22} \\ \end{array} \right]

A1A=E=AA1A^{-1}A=E=AA^{-1}
(首先是方陣)可逆矩陣(非奇異矩陣)的左逆等於右逆,乘積爲單位矩陣

奇異矩陣

首先看一下這個例子[1326]\begin{bmatrix}1&3\\2&6\\\end{bmatrix}它是否含有逆矩陣?
我們把逆矩陣看作對原矩陣的線性組合處理,那麼顯然我們找不到一種矩陣變化來將[1326]\begin{bmatrix}1&3\\2&6\\\end{bmatrix}變爲單位矩陣(兩行之間平行,兩列之間也平行,無法轉化爲E的形式),所以有存在任意兩行或兩列平行的矩陣爲奇異矩陣
或者我們可以換一種定義:如果一個方陣沒有逆,我們可以通過尋找一個非零向量X使得AX=0AX=0成立來描述。(線性相關性)比如上面的矩陣[1326]\begin{bmatrix}1&3\\2&6\\\end{bmatrix}對應的X是[31]\begin{bmatrix}3\\-1\end{bmatrix}
簡單的證明一下:
假設AA存在逆矩陣,那麼有A1AX=0A^{-1}AX=0,即X=0X=0,與題目所給的條件矛盾。

求解非奇異矩陣(Gauss-Jordan)

現在我們有[1327]\begin{bmatrix}1&3\\2&7\\\end{bmatrix}[acbd]=\begin{bmatrix}a&c\\b&d\\\end{bmatrix}=[1001]\begin{bmatrix}1&0\\0&1\\\end{bmatrix}這個方程,我們的目的就是求出對應的a,b,c,d,由上面的乘法思想我們使用列向量來處理:

[1327]\begin{bmatrix}1&3\\2&7\\\end{bmatrix}[ab]=\begin{bmatrix}a\\b\\\end{bmatrix}=[10]\begin{bmatrix}1\\0\\\end{bmatrix}[1327]\begin{bmatrix}1&3\\2&7\\\end{bmatrix}[cd]=\begin{bmatrix}c\\d\\\end{bmatrix}=[01]\begin{bmatrix}0\\1\\\end{bmatrix}於是問題又變成了解方程組的形式了。(Gauss-Jordan)只不過是同時解多個方程組。

先看看這樣的增廣矩陣[13102701]\left[\begin{array} {c c | c c} 1&3&1&0\\2&7&0&1\\\end{array} \right]是一種[AE]\begin{bmatrix}A&E\\\end{bmatrix}的形式,我們的目的是將其化成這樣的[EA1]\begin{bmatrix}E&A^{-1}\\\end{bmatrix}形式,而實際我們的變換的過程就相當於[A1][A^{-1}][AE]\begin{bmatrix}A&E\\\end{bmatrix}
實際變化一下有:

[1021]\begin{bmatrix}1&0\\-2&1\\\end{bmatrix}[13102701]=\left[\begin{array} {c c | c c} 1&3&1&0\\2&7&0&1\\\end{array} \right]=[13100121]\left[\begin{array} {c c | c c} 1&3&1&0\\0&1&-2&1\\\end{array} \right]

[1301]\begin{bmatrix}1&-3\\0&1\\\end{bmatrix}[1021]\begin{bmatrix}1&0\\-2&1\\\end{bmatrix}[13102701]=\left[\begin{array} {c c | c c} 1&3&1&0\\2&7&0&1\\\end{array} \right]=[10730121]\left[\begin{array} {c c | c c} 1&0&7&-3\\0&1&-2&1\\\end{array} \right]

即:[7321]\begin{bmatrix}7&-3\\-2&1\\\end{bmatrix}[13102701]=\left[\begin{array} {c c | c c} 1&3&1&0\\2&7&0&1\\\end{array} \right]=[10730121]\left[\begin{array} {c c | c c} 1&0&7&-3\\0&1&-2&1\\\end{array} \right][A1]([A^{-1}][AE]=[EA1]\begin{bmatrix}A&E\\\end{bmatrix}=\begin{bmatrix}E&A^{-1}\\\end{bmatrix})

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