Linear algebra identities of inverse matricies

In summary: Would I do the same thing for Aright? I'm paranoid because it seems the same but I'm asked about it as well so I expect it to be different.No, you would not do the same thing for Aright.
  • #1
SpiffyEh
194
0

Homework Statement


Left Inversion in Rectangular Cases. Let A[tex]^{-1}_{left}[/tex] = (A[tex]^{T}[/tex]A)[tex]^{-1}[/tex]A[tex]^{T}[/tex] show A[tex]^{-1}_{left}[/tex]A = I.

This matrix is called the left-inverse of A and it can be shown that if A [tex]\in[/tex] R[tex]^{m x n}[/tex] such that A has a pivot in every column then the left inverse exists.

Right Inversion in Rectangular Cases. Let A[tex]^{-1}_{right}[/tex] = A[tex]^{T}[/tex](AA[tex]^{T}[/tex])[tex]^{-1}[/tex]. Show AA[tex]^{-1}_{right}[/tex] = I.

This matrix is called the right-inverse of A and it can be shown that if A [tex]\in[/tex] R[tex]^{m x n}[/tex] such that A has a pivot in every row then the right inverse exists.

Homework Equations





The Attempt at a Solution


I tried the left part and this is what I did:
A[tex]^{-1}_{left}[/tex] / (A[tex]^{T}[/tex]A)[tex]^{-1}[/tex]= A[tex]^{T}[/tex]
A[tex]^{-1}_{left}[/tex](A[tex]^{T}[/tex]A) = A[tex]^{T}[/tex]
A[tex]^{-1}_{left}[/tex]A = A[tex]^{T}[/tex]( A[tex]^{T}[/tex])[tex]^{-1}[/tex] = I

I'm not sure if this is correct or not, so I want to see if I have the right idea. I know that A*A[tex]^{-1}[/tex] = I so I thought this would work. Also isn't the right one the exact same thing? Or do I have to do that one a different way? Oh and can someone also explain the concept of left and right inverse. I don't really understand it. Thanks
 
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  • #2
Sorry it's not showing right at all. I'll try to make it clearer. Al is A.

Attempt:
Al^(-1) / (A^T * A)^(-1) = A^T
Al^(-1) * (A^T * A) = A^T
Al^(-1) * A = A^T * (A^T)^(-1) = I
therefore, Al^(-1) * A = I

Hopefully that made what I was trying to do more clear

Can someone please help?
 
  • #3
Don't write divide when dealing with matrices, use the inverse notation.
Write the following to compute the inverse of [tex]A^{T}A[/tex]
[tex]
(A^{T}A)^{-1}(A^{T}A)=I
[/tex]
Multiply on the right by the appropriate stuff to find the expression for the inverse and then use this in the definition of the left inverse. I should come out in the wash.
 
  • #4
So, I did the (A[tex]^{T}[/tex]A)[tex]^{-1}[/tex](A[tex]^{T}[/tex]A) = I
and because of the property AA[tex]^{-1}[/tex] = I the left side is I. So, is this proff enough for Aleft? Is Aright basically the same thing then?
 
  • #5
I was trying to get you to show that
[tex]
(A^{T}A)^{-1}=A^{-1}(A^{T})^{-1}
[/tex]
Then use this in the definition of the left inverse to compute that
[tex]
A_{left}^{-1}A=I
[/tex]
 
  • #6
Are you allowed to assume that [itex]A^{-1}[/itex] and [itex](A^T)^{-1}[/itex] exist?
 
  • #7
Hmm, most likely not! my bad...
 
  • #8
And Spiffy, I think you're done in your proof.

Mat
 
  • #9
oh ok, thank you. Would I do the same thing for Aright? I'm paranoid because it seems the same but I'm asked about it as well so I expect it to be different.
 
  • #10
I think you'll be fine. Nothing to worry about.

Mat
 

Related to Linear algebra identities of inverse matricies

1. What are inverse matricies in linear algebra?

Inverse matricies are square matrices that, when multiplied by their corresponding matrix, result in an identity matrix. In other words, an inverse matrix "undoes" the original matrix.

2. What is the importance of inverse matricies in linear algebra?

Inverse matricies are important in many applications of linear algebra, such as solving systems of linear equations, calculating determinants, and finding solutions to matrix equations.

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

To find the inverse of a matrix, you can use various methods such as Gaussian elimination, Cramer's rule, or the adjugate matrix method. These methods involve performing operations on the original matrix to transform it into the identity matrix.

4. Can all matrices have an inverse?

No, not all matrices have an inverse. A matrix must be square and have a non-zero determinant in order to have an inverse. If a matrix does not meet these criteria, it is said to be singular and does not have an inverse.

5. Are inverse matricies unique?

Yes, inverse matricies are unique. This means that for a given matrix, there is only one inverse matrix that will result in an identity matrix when multiplied by the original matrix.

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