Inversion of this Vandermonde matrix

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Discussion Overview

The discussion revolves around the inversion of a Vandermonde matrix related to the discrete Fourier transform (DFT) and its application in extending a two-parameter function to three or more parameters. Participants explore the implications of using complex numbers in the function's expansion and the symmetry of the proposed formulations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant presents a matrix equation involving a Vandermonde matrix and seeks a closed-form expression for the vector x, recognizing it as a discrete Fourier transform.
  • Another participant confirms the approach and provides a solution in terms of the inverse of the matrix W, noting its properties as a Hermitian and unitary matrix.
  • A different participant questions the introduction of complex numbers in the function expansion, suggesting that the original function might be real-valued and pointing out the omission of odd parity permutations.
  • One participant expresses uncertainty about the usefulness of the decomposition of the multiparameter function, despite its symmetry and generalization potential.

Areas of Agreement / Disagreement

Participants generally agree on the mathematical framework involving the DFT and the properties of the matrix W. However, there is disagreement regarding the implications of using complex numbers in the function expansion and whether the proposed decomposition is beneficial.

Contextual Notes

Some assumptions about the nature of the function (real vs. complex) and the treatment of permutations in the expansion remain unresolved. The discussion also reflects varying interpretations of the symmetry and applicability of the proposed formulations.

Gerenuk
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I was trying to expand a three and more parameter functions similarly to the two-parameter case f(x,y)=(f(x,y)+f(y,x))/2+(f(x,y)-f(y,x))/2.

Anyway, to do the same for more parameters I need to solve
[tex] \begin{pmatrix}<br /> 1 & 1 & 1 & \dotsb & 1\\<br /> 1 & \omega & \omega^2 & \dotsb & \omega^{n-1}\\<br /> 1 & \omega^2 & \omega^4 & \dotsb & \omega^{2(n-1)}\\<br /> 1 & \omega^3 & \omega^6 & \dotsb & \omega^{3(n-1)}\\<br /> \vdots & &&& \vdots \\<br /> 1 & \omega^{n-1} & \omega^{2(n-1)} & \dotsb & \omega^{(n-1)(n-1)}<br /> \end{pmatrix}\mathbf{x}=<br /> \begin{pmatrix}<br /> 1 \\ 0 \\ 0 \\ 0 \\ \vdots \\ 0<br /> \end{pmatrix}[/tex]
with [itex]\omega=\exp(2\pi\mathrm{i}/n)[/itex]
Is there a closed form expression for x?

EDIT: Oh, silly me. I realized it's a discrete Fourier transform. So is this the correct way to expand then? In the 3 parameter case the solution would be
[tex] f(x,y,z)=\frac13(f(x,y,z)+f(y,z,x)+f(z,x,y))+\frac13\left(f(x,y,z)+\omega f(y,z,x)+\omega^*f(z,x,y)\right)+\frac13\left(f(x,y,z)+\omega^*f(y,z,x)+\omega f(z,x,y)\right)[/tex]
with [itex]\omega=\exp(2\pi\mathrm{i}/3)[/itex]?

Now I'm just wondering why I get linear dependent terms when I consider the real part only?
 
Last edited:
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You're on the right track. It is convenient to write this equation in matrix notation as

[tex]Wx=b[/tex]

where b is the vector you wrote on the RHS. Since W is full-rank and non-singular, it is invertible and the solution to your problem is

[tex]x=W^{-1}b[/tex] .

You need the inverse of W, but this is easy since we know from the properties of the discrete Fourier transform (DFT) that the individual vector columns of W are independent. Each is an orthonormal basis vector of the DFT. In words, this follows because the component of signal at one frequency (cosine or sine at w_m) is independent to that at every other frequency w_n. In fact,

[tex]W^{-1} = W^{\dagger}[/tex]

that is, W is Hermitian (the dagger is the conjugate transpose operation) and unitary (you get the identity matrix in the next equation)

[tex]WW^{\dagger}=I[/tex] .

You can perform this multiplication explicitly it to see that this is so. Accordingly

[tex]x=W^{\dagger}b[/tex]

and you can write out the components of x explicitly.
 
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I just wonder if that way to decompose a multiparameter function makes sense.

It's nicely symmetrical and generalizes to higher dimensions. However it introduces complex number where the initial function might actually be real only. And also I haven't included odd parity permutations of the function arguments...
 
Sorry, I'm not following your comments. I provided the closed solution to Wx=b, where W is complex, which was the question asked in your first post. Are you looking for something else?
 
I did that exercise to find a way to extend the rule f(x,y)=(f(x,y)+f(y,x))/2+(f(x,y)-f(y,x))/2 to higher dimensions (I didn't explain the connection; just mentioned it in the intro). I assumed some cyclic symmetry for the final form of f(x,y,z)=... and with the help of the discrete Fourier transform (which I didnt recognise at first), I can find some "decomposition".

Now I wasn't sure if the decomposition is useful this way.
 

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