Vandermonde Matrix, Polynomial Interpolation & Orthogonal Basis

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SUMMARY

The discussion focuses on the relationship between the Vandermonde matrix, polynomial interpolation, and orthogonal bases. It highlights that the monomial basis is not optimal due to its lack of orthogonality, which contributes to the ill-conditioning of the Vandermonde matrix. The participants seek clarity on why orthogonal bases lead to better-conditioned problems and how this principle applies in practice. Key insights include the importance of orthogonality in isolating effects within polynomial interpolation.

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  • Understanding of polynomial interpolation techniques
  • Familiarity with the properties of the Vandermonde matrix
  • Knowledge of orthogonal bases in linear algebra
  • Basic matrix operations and transformations
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azay
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In polynomial interpolation:

I see some connection between:

The Vandermonde matrix, the monomial basis and the fact that 'the monomial basis is not a good basis because it's components are not very orthogonal'.

Now, I still don't really grasp sufficiently the reason why exactly a Vandermonde matrix is often ill-conditioned. Also, I don't feel I understand why an orthogonal basis in general leads to better conditioned problems, how self-evident it may look from a certain point of view.

Any insights?
 
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Here is a rapid insight,
Obtain, the vector below, at each cases
\left[\begin{array}{cc}1 &0\\0 &1\end{array}\right]\left(\begin{array}{c}x\\y\end{array}\right)= \left(\begin{array}{c}3\\5\end{array}\right)


\left[\begin{array}{cc}1 &-1\\1 &1\end{array}\right]\left(\begin{array}{c}x\\y\end{array}\right)= \left(\begin{array}{c}3\\5\end{array}\right)

Please repeat it for the vector \left(\begin{array}{c}3.1\\5\end{array}\right)

You can relate orthogonality to being able to isolate arbitrary effects to one subset of orthogonal elements. Usually, complicated things are just for simplicity...
 

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