Find the QR Factorization of a matrix

In summary: If it's not, you've done something wrong. In summary, the conversation discusses finding the QR factorization for a 4x3 matrix and the solution provided by the individual. The individual's solution includes a Q matrix with four columns instead of the required three, and a R matrix that does not satisfy the requirements for an orthogonal matrix. Despite discrepancies, the individual and their professor believe their solution to be correct.
  • #1
badvash88
5
0

Homework Statement


Find the QR factorization for the 4x3 matrix M
1 1 0
1 0 2
1 0 1
1 1 1

Homework Equations


M = QR

The Attempt at a Solution


I got the first two columns of Q correct, but I am getting the third wrong for some reason beyond me.
for Q, i got u1= 1/2 (1, 1, 1, 1) (vertical, not horizontal)
and u2 = 1/2 (1, -1, -1, 1) (once again vertical, not horizontal, don't know how to make matrices easily on here)
I got R correct except for the last number in the bottom right, need v3perp.thanks
 
Last edited:
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  • #2
anyone?
 
  • #3
Q=[-0.5 0.5 -0.5 -0.5; -0.5 -0.5 0.5 -0.5; -0.5 -0.5 -0.5 0.5; -0.5 0.5 0.5 0.5]
r=[-2 -1 -2; 0 1 -1; 0 0 1; 0 0 0]
 
  • #4
your matrices answers seem to big. there should only be three columns in Q

are you sure those are right. i got the answer not the solution and my u1 and u2 are the same as that, but its my u3 that is wrong. it says it is (-3/2, 3/2, 1/2, 1/2)
 
  • #5
Before we decide to correct my work, let's multiply Q and R, something you could've done with your Q and R to see your mistake


>> [-0.5 0.5 -0.5 -0.5; -0.5 -0.5 0.5 -0.5; -0.5 -0.5 -0.5 0.5; -0.5 0.5 0.5 0.5]*[-2 -1 -2; 0 1 -1; 0 0 1; 0 0 0]

ans =

1 1 0
1 0 2
1 0 1
1 1 1
 
  • #6
ahh but you are wrong. you have TOO MANY columns. there are only three columns in Q and you just added a row in R to make M work.
i just figure my solution is correct and the soltion book is wrong
Q is
.5 .5 -.5
.5 -.5 .5
.5 -.5 -.5
.5 .5 .5

R is
2 1 2
0 1 -1
0 0 1

that equals M
so i believe that is right.
thanks anyways tho
 
  • #7
Ok then..
 
  • #8
You know that Q is supposed to be an orthogonal matrix, right? So if your Q isn't square, you've done something wrong.
 
  • #9
nah man. Q is fine. R is the orthogonal matrix i believe. or at least it is always squared
my professor and another solution book both verified my answer.

thanks you guys, but this problem is good
/thread
 
  • #10
I haven't checked your solution, but no, Q is the orthogonal matrix... so it needs to be 4 by 4.
 

Related to Find the QR Factorization of a matrix

1. What is the QR Factorization of a matrix?

The QR Factorization of a matrix is a mathematical process used to decompose a matrix into two components: an orthogonal matrix (Q) and an upper triangular matrix (R). This factorization can be used for solving systems of linear equations, least squares problems, and other numerical computations.

2. How is the QR Factorization of a matrix calculated?

The QR Factorization of a matrix is calculated using the Gram-Schmidt process, which involves orthogonalizing the columns of the matrix to form the Q matrix and then using this orthogonalized matrix to calculate the upper triangular matrix, R.

3. What is the significance of the QR Factorization in linear algebra?

The QR Factorization is significant in linear algebra because it provides a way to solve systems of linear equations without using matrix inversion, which can be computationally expensive. It is also used in other applications such as data fitting and signal processing.

4. Can any matrix be factorized using the QR Factorization method?

No, not all matrices can be factorized using the QR Factorization method. The matrix must have linearly independent columns in order for the factorization to be possible.

5. How is the QR Factorization used in practical applications?

The QR Factorization is used in a variety of practical applications, such as image processing, data compression, and machine learning. It is also commonly used in numerical methods for solving differential equations and other mathematical problems.

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