Find Inverse of Matrix Homework Statement

In summary, the conversation discussed the concept of a matrix inverse, how to find the inverse of a matrix, the importance of finding the inverse, and the conditions for a matrix to be invertible. It was also mentioned that non-square matrices do not have an inverse.
  • #1
Telemachus
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Homework Statement



I have to find the inverse for this generic matrix (the dimensions are not specified, but I assume its a square matrix, I don't know if that is necessary).

##A=\left [
\begin{matrix}
1 & -1 & -1 & -1 & \dots & -1 & -1 \\
0 & 1 & -1 & -1 & \dots & -1 & -1 \\
0 & 0 & 1 & -1 & \dots & -1 & -1 \\
\vdots & \vdots & \vdots & \vdots & \ddots & \vdots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##

I think there must be a clever and fast way for calculating ##A^{-1}##, but I don't know how to do it.

Thanks in advance.
 
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  • #2
It is necessary that matrix A be square for an inverse to exist.

It's not clear why you need to calculate the inverse. Are you trying to solve a system of linear equations?

In any event, the matrix A is a special kind of triangular matrix called an atomic triangular matrix, and there is a simple and easy method of calculating its inverse.
See this article for the details:

https://en.wikipedia.org/wiki/Triangular_matrix
 
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  • #3
No, it's just an exercise. It asks explicitly to give the inverse Matrix.

Thank you verymuch :)

One detail, it's not an atomic matrix, is just upper triangular.
 
Last edited:
  • #4
Telemachus said:
No, it's just an exercise. It asks explicitly to give the inverse Matrix.

Thank you verymuch :)

One detail, it's not an atomic matrix, is just upper triangular.
I see that now. Sorry.
 
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  • #5
No problem. I did it my way, I think its okey. I've assumed an ##n \times n## matrix, and found:

##A^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 3 & \dots & n-2 & n-1 \\
0 & 1 & 1 & 2 & \dots & n-3 & n-2 \\
0 & 0 & 1 & 1 & \dots & n-4 & n-3 \\
\vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##

This is not right, I get trouble after the third column.
 
Last edited:
  • #6
Telemachus said:
No problem. I did it my way, I think its okey. I've assumed an ##n \times n## matrix, and found:

##A^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 3 & \dots & n-2 & n-1 \\
0 & 1 & 1 & 2 & \dots & n-3 & n-2 \\
0 & 0 & 1 & 1 & \dots & n-4 & n-3 \\
\vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##

This is not right, I get trouble after the third column.
Instead of jumping right into n x n matrices, start with smaller matrices. I looked at the case with a 3 x 3 matrix, and then with a 4 x 4 matrix. There's a definite pattern that develops.
 
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  • #7
Yes, I've tried that way, but wasn't that clear to me. The case for the ##3\times3## is contained in the first 3 rows and columns.

##A_{3\times3}^{-1}
=\left [
\begin{matrix}
1 & 1 & 2 \\
0 & 1 & 1 \\
0 & 0 & 1 \\
\end{matrix}
\right]##

Then for the ##4\times 4##:
##A_{4\times4}^{-1}=
=\left [
\begin{matrix}
1 & 1 & 2 & 4\\
0 & 1 & 1 & 2 \\
0 & 0 & 1 & 1 \\
0 & 0 & 0 & 1 \\
\end{matrix}
\right]##

And for ##5\times5##

##A_{5\times5}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 4 & 8\\
0 & 1 & 1 & 2 & 4 \\
0 & 0 & 1 & 1 & 2 \\
0 & 0 & 0 & 1 & 1 \\
0 & 0 & 0 & 0 & 1 \\
\end{matrix}
\right]##

Then:

##A_{n\times n}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 3 & \dots & 2^{n-3} & 2^{n-2} \\
0 & 1 & 1 & 2 & \dots & 2^{n-4} & 2^{n-3} \\
0 & 0 & 1 & 1 & \dots & 2^{n-5} & 2^{n-4} \\
\vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##
 
Last edited:
  • #8
Telemachus said:
Yes, I've tried that way, but wasn't that clear to me. The case for the ##3\times3## is contained in the first 3 rows and columns.

##A_{3\times3}^{-1}
=\left [
\begin{matrix}
1 & 1 & 2 \\
0 & 1 & 1 \\
0 & 0 & 1 \\
\end{matrix}
\right]##

Then for the ##4\times 4##:
##A_{4\times4}^{-1}=
=\left [
\begin{matrix}
1 & 1 & 2 & 4\\
0 & 1 & 1 & 2 \\
0 & 0 & 1 & 1 \\
0 & 0 & 0 & 1 \\
\end{matrix}
\right]##

And for ##5\times5##

##A_{5\times5}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 4 & 8\\
0 & 1 & 1 & 2 & 4 \\
0 & 0 & 1 & 1 & 2 \\
0 & 0 & 0 & 1 & 1 \\
0 & 0 & 0 & 0 & 1 \\
\end{matrix}
\right]##

Then:

##A_{n\times n}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 3 & \dots & 2^{n-3} & 2^{n-2} \\
0 & 1 & 1 & 2 & \dots & 2^{n-4} & 2^{n-3} \\
0 & 0 & 1 & 1 & \dots & 2^{n-5} & 2^{n-4} \\
\vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##

So, was your original matrix
[tex] \left[ \begin{matrix} 1 & -1 & -1 & -1 \\
0 & 1 & -1 & -1 \\
0 & 0 & 1 & -1 \\
0 & 0 & 0 & 1
\end{matrix} \right]
[/tex]
not what was intended? When did the switch occur?
 
  • #9
Ray Vickson said:
So, was your original matrix
[tex] \left[ \begin{matrix} 1 & -1 & -1 & -1 \\
0 & 1 & -1 & -1 \\
0 & 0 & 1 & -1 \\
0 & 0 & 0 & 1
\end{matrix} \right]
[/tex]
not what was intended? When did the switch occur?
The original matrix was n X n, not 4 X 4.
 
  • #10
Telemachus said:
And for ##5\times5##

##A_{5\times5}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 4 & 8\\
0 & 1 & 1 & 2 & 4 \\
0 & 0 & 1 & 1 & 2 \\
0 & 0 & 0 & 1 & 1 \\
0 & 0 & 0 & 0 & 1 \\
\end{matrix}
\right]##

Then:

##A_{n\times n}^{-1}=\left [
\begin{matrix}
1 & 1 & 2 & 3 & \dots & 2^{n-3} & 2^{n-2} \\
0 & 1 & 1 & 2 & \dots & 2^{n-4} & 2^{n-3} \\
0 & 0 & 1 & 1 & \dots & 2^{n-5} & 2^{n-4} \\
\vdots & \vdots & \vdots & \vdots & \vdots & \ddots & \vdots \\
0 & 0 & 0 & 0 & \dots & 0 & 1 \\
\end{matrix}
\right]##
Your last matrix isn't following the pattern of the previous ones. Check the first row in the matrix just above.
 
  • #11
Mark44 said:
The original matrix was n X n, not 4 X 4.

Yes, I know. But the OP did some 3x3 and 4x4 examples, and I was just looking at the 4x4 case.
 
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  • #12
Its done. I did as Mark said, by trying some tractable dimensions, and then generalized it. Thanks.
 
  • #13
Mark44 said:
Your last matrix isn't following the pattern of the previous ones. Check the first row in the matrix just above.
That 3 was just a typo. Sorry.
 

Related to Find Inverse of Matrix Homework Statement

1. What is a matrix inverse?

A matrix inverse is a matrix that when multiplied with the original matrix results in the identity matrix.

2. How do you find the inverse of a matrix?

To find the inverse of a matrix, you can use the Gauss-Jordan elimination method or the adjugate method. Both methods involve manipulating the matrix through various operations until it is transformed into the identity matrix.

3. Why is finding the inverse of a matrix important?

The inverse of a matrix is important because it allows us to solve systems of linear equations, calculate determinants, and perform other mathematical operations that would otherwise be difficult or impossible without it.

4. Are all matrices invertible?

No, not all matrices are invertible. Only square matrices that have a non-zero determinant are invertible. Matrices with a determinant of 0 are not invertible and are referred to as singular matrices.

5. Can you find the inverse of a non-square matrix?

No, the inverse of a matrix can only be found if the matrix is square. Non-square matrices do not have an inverse.

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