Linear Algebra lecture8 note

Compute solution of AX=b (X=Xp+Xn)

rank r

r=m solutions exist

r=n solutions unique

 



example:

若想方程有解,b1,b2,b3需要满足什么条件? 观察矩阵可知,第三行是前两行的和,所以b1+b2=b3

Solvability Condition on b:

Ax=b is solvable when b is in C (A)

If a combination of Rows of A gives zero row, then the same combination of entries of b must give 0

假设,则上述矩阵变为:

To find complete solution to AX=b:

1.Xp (particular): set all free variables to zero, solve AX=b for pivot variable

此例中,X2=0,X4=0

2.Xn(nullspace) 上一节已经解出

3.X(complete)=Xp+Xn

以上操作可解释为:

 



m by n matrix A of rank r(r<=m,r<=n)

Full column of rank(r=n):

所有列均有主元; no free variables;  N(A)=zero vector; solution to AX=b is X=Xp which means if solution exists then the solution is unique(0 or 1 solution)

这种情况实际就是,除zero组合之外,列之间的线性组合无法产生零列

Full row of rank(r=m):

所有行均有主元; no zero rows; can solve AX=b for every b; left with n-r(n-m) free variables

Full rank(r=m=n):

N(A)=zero vector; R(行最简形)=I(单位矩阵)

 

summary:

矩阵的秩决定了方程组解的数目

时间: 2024-10-12 02:28:45

Linear Algebra lecture8 note的相关文章

Linear Algebra lecture4 note

Inverse of AB,A^(A的转置) Product of elimination matrices  A=LU (no row exchanges)   Inverse of AB,A^(A的转置):   Product of elimination matrices  A=LU (no row exchanges) E32E31E21A=U (no row exchanges)    EA=U A=E21`E31`E32`U L表示下三角矩阵,lower triangle D表示对角

MAT2040 Linear Algebra

Binary Vector Spaces and Error Correcting CodesMAT2040 Linear Algebra (2019 Fall)Project 1Project Instructions:• Read the following text and answer the questions given in and after the text.• For questions that need Julia, both codes and results shou

A Linear Algebra Problem(唯一性的判定)

A Linear Algebra Problem Time Limit: 3000/1000MS (Java/Others)     Memory Limit: 65535/65535KB (Java/Others) Submit Status God Kufeng is the God of Math. However, Kufeng is not so skilled with linear algebra, especially when dealing with matrixes. On

《Linear Algebra and Its Applications》- 线性方程组

同微分方程一样,线性代数也可以称得上是一门描述自然的语言,它在众多自然科学.经济学有着广阔的建模背景,这里笔者学识有限暂且不列举了,那么这片文章来简单的讨论一个问题——线性方程组. 首先从我们中学阶段就很熟系的二元一次方程组,我们采用换元(其实就是高斯消元)的方法.但是现在我们需要讨论更加一般的情况,对于线性方程,有如下形式: a1x1+a2x2+…anxn = b. 现在我们给出多个这样的方程构成方程组,我们是否有通用的解法呢? 在<Linear Algebra and Its Applica

Here’s just a fraction of what you can do with linear algebra

Here’s just a fraction of what you can do with linear algebra The next time someone wonders what the point of linear algebra is, send them here. I write a blog on math and programming and I see linear algebra applied to computer science all the time.

Memo - Chapter 6 of Strang&#39;s Linear Algebra and Its Applications

1.实对称矩阵的正定 2.实对称矩阵的半正定 3. Sylvester’s law of inertia : 4.Sylvester’s law of inertia 的推论: 5. SVD 6.瑞利伤: Memo - Chapter 6 of Strang's Linear Algebra and Its Applications

Memo - Chapter 3 of Strang&#39;s Linear Algebra and Its Applications

1.正交向量.正交空间.正交补空间 2.号称是本书最重要的配图 3.向量的cosine距离,投影变换,最小二乘 4.正交基与Schmidt正交化与QR分解 5.函数空间,傅里叶级数,Hilbert空间 Memo - Chapter 3 of Strang's Linear Algebra and Its Applications

cdoj793-A Linear Algebra Problem

http://acm.uestc.edu.cn/#/problem/show/793 A Linear Algebra Problem Time Limit: 3000/1000MS (Java/Others)     Memory Limit: 65535/65535KB (Java/Others) Submit Status God Kufeng is the God of Math. However, Kufeng is not so skilled with linear algebra

《Linear Algebra and Its Applications》-矩阵运算

可以说第一章<Linear Algebra and Its Applications>着重介绍了线性代数中几个核心概念(向量.矩阵和线性方程组)之间的关系(方程的同解性),那么下面这本书开始分别介绍这几个核心概念,比如从这篇文章开始,会简单的介绍矩阵方面的内容. 首先对于我们定义的计算工具(矩阵),我们有必要研究其运算规律,这个方法在定义很多新的运算符号的时候都是适用的.矩阵的加减法这里就不用累述的,非常好理解,这篇文中我们主要来讨论矩阵的乘法运算的定义过程. 其实不管是从离散的角度还是在线性