05 MIT线性代数-转置,置换,向量空间Transposes, permutations, spaces

1. Permutations P:

execute row exchanges

becomes PA = LU for any invertible A

Permutations P = identity matrix with reordered rows

m=n (n-1) ... (3) (2) (1) counts recordings, counts all nxn permuations

对于nxn矩阵存在着n!个置换矩阵

p^{-1}=p^{T}p^{T}p^{-1}=I

2. Transpose:

05 MIT线性代数-转置,置换,向量空间Transposes, permutations, spaces_第1张图片

(A^{T})_{ij}=A_{ji}

2.1 Symmetric matrices

对称矩阵 A^{T}=A

2.2 矩阵乘积的转置

 (AB)^{T}=B^{T}A^{T}

2.3 R^{T}R is always symmetric

why? take transpose (R^{T}R)^{T}=R^{T}(R^{T})^{T}=R^{T}R

3. 向量空间 Vector spaces

向量空间对线性运算封闭,即空间内向量进行线性运算得到的向量仍在空间之内

example: R^{2}= all 2-dim real vectors=x-y plane

first component, second component

 R^{3} = all vectors with 3 components

 R^{m} = all column vectors with m real components

所有向量空间必然包含零向量,因为任何向量数乘0或者加上反向量都会得到零向量,而因为向量空间对线性运算封闭,所以零向量必属于向量空间

反例 not a vector space: 

 R^{2} 中的第一象限则不是一个向量空间, 加法数乘不封闭

4. 子空间 Subspaces

a vector space inside R^{2}, subspace of R^{2}

line in R^{2} through zero vector

反例:

R^{2}中不穿过原点的直线就不是向量空间。子空间必须包含零向量,原因就是数乘0的到的零向量必须处于子空间中

subspaces of R^{2}:

1. all of R^{2}

2. any line through \begin{vmatrix} 0\\ 0 \end{vmatrix}  L(line)

3. zero vector only z(zero)

subspaces of R^{3}:

1. all of R^{3}

2. any plane through \begin{vmatrix} 0\\ 0 \\0 \end{vmatrix} P(plane)

2. any line through \begin{vmatrix} 0\\ 0 \\0 \end{vmatrix}  L(line)

3. zero vector only z(zero) = \left \{\begin{vmatrix} 0\\ 0 \\0 \end{vmatrix} \right \}

05 MIT线性代数-转置,置换,向量空间Transposes, permutations, spaces_第2张图片

5. 列空间 Column spaces

Columns in R^{3}: all their combinations from a subspace called column space C(A)
05 MIT线性代数-转置,置换,向量空间Transposes, permutations, spaces_第3张图片

空间内包含两向量的所有线性组合

05 MIT线性代数-转置,置换,向量空间Transposes, permutations, spaces_第4张图片

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