Hello,The pseudoinverse formula for a matrix A is given by:P =

In summary, the pseudoinverse formula for a matrix A is (A^{T}A)^{-1}A^{T}. It is not guaranteed to exist, as shown in the example A = [1 1] [0 0]. It is useful for matrices of rank k, where ATA is an invertible kxk matrix. The pseudo-inverse acts as a left-inverse for A, serving as a substitute for the inverse in cases where it does not exist.
  • #1
pamparana
128
0
Hello,

The pseudoinverse formula for a matrix A is given by:

P = (A[itex]^{T}[/itex]A)[itex]^{-1}[/itex]A[itex]^{T}[/itex]

I remember knowing this some time ago and this has me worried now...why is (A[itex]^{T}[/itex]A)[itex]^{-1}[/itex] guaranteed to exist? I know it is a square matrix but it could still be degenerate, right?

Would appreciate any help.

Thanks,
Luca
 
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  • #2


it's not guaranteed to exist.

for example, consider A =

[1 1]
[0 0].

the (left) pseudoinverse is useful when you have an nxk matrix (n > k) of rank k. then ATA is an invertible kxk matrix, so

(ATA)-1AT acts as a left-inverse (to the left-identity) for A, as you can easily verify by computation.

(in this case, In is merely a left-identity for the nxk matrices, the right-identity is Ik, and these matrices are of different sizes).

in other words, the pseudo-inverse "acts" like an inverse on a class of matrices which don't have inverses.
 

1. What is a pseudoinverse?

The pseudoinverse of a matrix A is a generalization of the inverse matrix that can be applied to non-square matrices. It is denoted by A+ and satisfies the equation AA+A = A.

2. When is a pseudoinverse used?

A pseudoinverse is used when the matrix A is not invertible, meaning it does not have a traditional inverse. It is also used in cases where the matrix is over-determined or under-determined.

3. How is the pseudoinverse formula derived?

The pseudoinverse formula is derived using the singular value decomposition (SVD) of a matrix. The pseudoinverse is defined as the transpose of the matrix of right singular vectors multiplied by the inverse of the diagonal matrix of singular values, multiplied by the transpose of the matrix of left singular vectors.

4. What are the properties of the pseudoinverse?

The pseudoinverse has several important properties, including being a left and right inverse, meaning A+A = I and AA+ = I. It is also unique and is the best approximation of the inverse for non-invertible matrices.

5. How is the pseudoinverse used in practical applications?

The pseudoinverse is used in a variety of practical applications, including solving systems of linear equations, data fitting, and image processing. It is also used in machine learning algorithms, such as linear regression and principal component analysis.

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