Matrix proof - augmented matrix - row reduction - column operation - proof

In summary, the equations in the homework statement have no solutions, and if c_1,...,c_n are the columns of A, then c_{n+1} is not a linear combination of c_1,...,c_n.
  • #1
maximus101
22
0

Homework Statement



If we let A be the augmented m x (n + 1) matrix of a system of m linear equations
with n unknowns

Let B be the m x n matrix obtained from A by removing the last
column.

Let C be the matrix in row reduced form obtained from A by elementary
row operations.

Prove the the following statements are equivalent:

(i) The linear equations have no solutions

(ii) If [tex]c_1[/tex],..., [tex]c_{n+1}[/tex] are the columns of A, then [tex]c_{n+1}[/tex] is not a linear combination of
[tex]c_1[/tex],..., [tex]c_n[/tex]


Homework Equations





The Attempt at a Solution



I'm not sure were to start, some good advice would help and then I can use it - comment back

thank you
 
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  • #2
You could start by finding some examples for yourself, this should give you a hint about what's going on.

Now, assume that [tex]c_1,...,c_{n+1}[/tex] are linearly dependent. This means that

[tex]\alpha_1 c_1+...+\alpha_n c_n=c_{n+1}[/tex]

for some [tex]\alpha_1,...,\alpha_n[/tex]. This determines a system of m equations. Can you tell me what that system is?
 
  • #3
micromass said:
You could start by finding some examples for yourself, this should give you a hint about what's going on.

Now, assume that [tex]c_1,...,c_{n+1}[/tex] are linearly dependent. This means that

[tex]\alpha_1 c_1+...+\alpha_n c_n=c_{n+1}[/tex]

for some [tex]\alpha_1,...,\alpha_n[/tex]. This determines a system of m equations. Can you tell me what that system is?

Okay I think perhaps from this information I could get

[tex]a_1[/tex][tex]c_1[/tex] = [tex]c_{n+1}[/tex] - [tex]a_2[/tex][tex]c_2[/tex] - [tex]a_3[/tex][tex]c_3[/tex] - ... - [tex]a_n[/tex][tex]c_n[/tex]

and then do this for [tex]c_2[/tex] ... [tex]c_n[/tex] and have n equations

but I'm not sure how we would get a system of m equations from this,

unles we made a matrix with m rows. Also I see the value of [tex]a_{n+1}[/tex] = -1 ?
 
  • #4
Note that [tex]c_1,...,c_{n+1}[/tex] are columns of a matrix. This means that they are just row matrices with m rows.
So, what you should do, is to write [tex]c_1,...,c_{n+1}[/tex] explicitly as row matrices and to regard the equation

[tex]\alpha_1 c_1+...+\alpha_n c_n=c_{n+1}[/tex]

if you exchange every ci by its actual form as a row matrix. You will see m equations popping up...
 
  • #5
micromass said:
Note that [tex]c_1,...,c_{n+1}[/tex] are columns of a matrix. This means that they are just row matrices with m rows.
So, what you should do, is to write [tex]c_1,...,c_{n+1}[/tex] explicitly as row matrices and to regard the equation

[tex]\alpha_1 c_1+...+\alpha_n c_n=c_{n+1}[/tex]

if you exchange every ci by its actual form as a row matrix. You will see m equations popping up...

okay I think I understand a bit better, so considering c1 this will form the
first colum of A and it will have m rows, so we will have these equations, for the first row
of A it will be

c11c1 + c21c2 + ... + cn1cn = c(n+1)1

were cij s.t. i=column j=row

and the second will be

c12c1 + c22c2 + ... + cn2cn = c(n+1)2


we will get a series of m of there since the matrix A has m rows?
 
  • #6
What is probably troubling you is that [tex]c_1[/tex] is a matrix. Thus, in fact:

[tex]c_i=\left(\begin{array}{c}c_{1,i}\\ c_{2,i}\\ \vdots\\ c_{m,i}\end{array}\right)[/tex]

So if you want to calculate the following:

[tex]\alpha_1c_1+...+\alpha_nc_n=c_{n+1}[/tex]

then you are actually calculating

[tex]\alpha_1 \left(\begin{array}{c}c_{1,1}\\ c_{2,1}\\ \vdots\\ c_{m,1}\end{array}\right)+\alpha_2 \left(\begin{array}{c}c_{1,2}\\ c_{2,2}\\ \vdots\\ c_{m,2}\end{array}\right)+ \hdots + \alpha_n \left(\begin{array}{c}c_{1,n}\\ c_{2,n}\\ \vdots\\ c_{m,n}\end{array}\right)=\left(\begin{array}{c}c_{1,n+1}\\ c_{2,n+1}\\ \vdots\\ c_{m,n+1}\end{array}\right)[/tex]

So, what happens if you make this addition?
 
  • #7
micromass said:
What is probably troubling you is that [tex]c_1[/tex] is a matrix. Thus, in fact:

[tex]c_i=\left(\begin{array}{c}c_{1,i}\\ c_{2,i}\\ \vdots\\ c_{m,i}\end{array}\right)[/tex]

So if you want to calculate the following:

[tex]\alpha_1c_1+...+\alpha_nc_n=c_{n+1}[/tex]

then you are actually calculating

[tex]\alpha_1 \left(\begin{array}{c}c_{1,1}\\ c_{2,1}\\ \vdots\\ c_{m,1}\end{array}\right)+\alpha_2 \left(\begin{array}{c}c_{1,2}\\ c_{2,2}\\ \vdots\\ c_{m,2}\end{array}\right)+ \hdots + \alpha_n \left(\begin{array}{c}c_{1,n}\\ c_{2,n}\\ \vdots\\ c_{m,n}\end{array}\right)=\left(\begin{array}{c}c_{1,n+1}\\ c_{2,n+1}\\ \vdots\\ c_{m,n+1}\end{array}\right)[/tex]




So, what happens if you make this addition?

okay thanks, that is a lot more clear now


we will have m equations:

[tex]\alpha_1c_{1,1}+...+\alpha_nc_{1,n}=c_{1,(n+1)}[/tex]

.
.
.
.

[tex]\alpha_1c_{m,1}+...+\alpha_nc_{m,n}=c_{m,(n+1)}[/tex]

we assumed linear dependence, so I think we are trying to prove by counterexample
that linear dependence is not possible which imples the statement is true. So perhaps we must show next that these
[tex]a_1,a_2,...,a_n[/tex] do not exist such that this system holds?
 
  • #8
ok I get it now, we got the system of equations and we showed that (ii) holds

is the same as saying there is no solutions of the linear equations which is exactly what one says (i) ?
 
  • #9
if this is correct, could you possibly explain how Rank (A) > Rank (B)

where B is the m x n matrix we get from A by removing the last column .
 

1. What is a matrix proof?

A matrix proof is a mathematical method of verifying the validity of a statement or equation using matrices. It involves manipulating matrices through various operations to demonstrate that the given statement is true or false.

2. What is an augmented matrix?

An augmented matrix is a matrix that contains both the coefficients and the constants of a system of linear equations. It is represented by placing a vertical bar between the coefficient matrix and the constant matrix.

3. What is row reduction?

Row reduction, also known as Gaussian elimination, is a method of simplifying a system of linear equations by performing a series of row operations on the augmented matrix. These row operations include multiplying a row by a constant, adding a multiple of one row to another, and interchanging two rows.

4. What are column operations?

Column operations are similar to row operations, but they are applied to the columns of a matrix instead of the rows. These operations include multiplying a column by a constant, adding a multiple of one column to another, and interchanging two columns.

5. How are these concepts used in proofs?

Matrix proof, augmented matrix, row reduction, and column operations are all used in various ways to demonstrate the validity of mathematical statements. These concepts allow us to manipulate matrices in a systematic manner to simplify equations and solve systems of linear equations, making it easier to prove or disprove mathematical statements.

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