MIT公开课-线性代数笔记

2018-12-11 21:10

目录

方程组的几何解释 ................................................................................................................ 4 矩阵消元 ............................................................................................................................... 4 乘法和逆矩阵 ....................................................................................................................... 6 A的LU分解......................................................................................................................... 7 转置-置换-向量空间R .......................................................................................................... 9 求解AX=0:主变量,特解................................................................................................. 10 求解AX=b:可解性和解的解构 ......................................................................................... 11 线性相关性、基、维数 ....................................................................................................... 13 四个基本子空间 .................................................................................................................. 14 矩阵空间、秩1矩阵和小世界图 ........................................................................................ 15 图和网络 ............................................................................................................................. 16 正交向量与子空间 .............................................................................................................. 17 子空间投影 ......................................................................................................................... 20 投影矩阵与最小二乘 .......................................................................................................... 22 正交矩阵和Gram-Schmidt正交化 ..................................................................................... 23 特征值与特征向量 .............................................................................................................. 29 对角化和A的幂 ................................................................................................................. 30 微分方程和exp(At)(待处理) .......................................................................................... 31 对称矩阵与正定性 .............................................................................................................. 31 正定矩阵与最小值 .............................................................................................................. 33 相似矩阵和若尔当型(未完成) ........................................................................................ 34

奇异值分解(SVD) ............................................................................................................... 35 线性变换及对应矩阵 .......................................................................................................... 36 基变换和图像压缩 .............................................................................................................. 38

NOTATION p:projectionvector P:projectionmatrix e:errorvector P:permutationmatrix

T:transport sign

C(A):columnspace N(A):null space U:uppertriangular L:lower triangular E:elimination matrix

Q:orthogonalmatrix, which the

means column vectors are orthogonal

E:elementary/elimination matrix, which always appears in the elimination of matrix N:null space matrix, the “solution matrix” of AX=0

R:reduced matrix, which always appears in the triangular matrix, “IF00” I:identity matrix S:eigenvector matrix Λ:eigenvalue matrix C:cofactor matrix

关于LINER ALGEBA名垂青史的分析方法: 由具象到抽象,由二维到高维。

方程组的几何解释

1. 行图像,列图像 2. 矩阵乘法:

方法一. 列向量的线性组合 方法二. 左行乘以右列

3. 矩阵右乘向量(竖直):矩阵列的线性组合 4. 矩阵左乘向量(横平):矩阵行的线性组合

矩阵消元

1. 课程目标:讨论消元法有效,以及无效的情况 用矩阵语言描述消元法

2. 消元有效和失效

a) 消元目标:把A矩阵化为U矩阵(主元不能出现0) b) 消元失效:主元是0:行交换可以解决主元为0的暂时性失效,但当底下的行中再也没有非0元素时,消元就彻底失效了。 3. 用矩阵来表示矩阵变换(消元) a) 例

?121??100??121???????目的:从r2中减去3倍r1381???????????310381????????041??001??041???????E21?121??100??121???????目的:从r3中减去2倍r202?2??????????01002-2??????

?0-21??005??041???????E32?100???310b) 针对上一例,假设总变换E=E32E21,E????,这个?6?21???矩阵对于消元法中出现的乘数来说太不直观了,然而E-1=E21-1E32-1,这个逆比较直观,因为它们是初等列变换的逆变换,只用改变乘数的系数就可以得到它们的逆,这就引出了下一章的内容:A的LU分解。

?|?|??|?|?||||||||?-??-?-??-

?|?|??|?|?----

?a??|??|??|??|???????????b|||??=a??+b??+c??+d?|? ?c??|??|??|??|????????????d??|??|??|??|??abcd?----

-?

?-?-??-?

=a??????+b??????+c??????+d?????? 4. 置换矩阵


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