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Luna947
  • Member for 2 years, 5 months
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prove spectral equivalence bounds for inverse fractional power of matrices
Thank you very much for the fruitful information that you provided to me. It was really interesting learning about Loewner's theorem and a great help for closing some remaining gaps in my thesis!
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prove spectral equivalence bounds for inverse fractional power of matrices
sorry maybe i formulated the constant to sloppy. We know $x^\top A x \le c^+ x^\top D x$ and $x^\top A^{-1} x \le \frac{1}{c^-} x^\top D^{-1} x$ holds. Doesn't the addition of both inequalities yield $x^\top (A+A^{-1}) x = x^\top A x + x^\top A^{-1} x \le c^+ x^\top D x + \frac{1}{c^-} x^\top D^{-1} x \le \max\{c^+, 1/c^-\} x^\top (D + D^{-1}) x$ ?
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prove spectral equivalence bounds for inverse fractional power of matrices
And let me come up with another question - i think that should be the last one! Is it possible to make a statement concerning the spectral equivalence estimates of the sum, e.g., something like $(A+A^{-1}) \le \max\{c^+, \frac{1}{c^+}\} (D + D^{-1})$ based on the bounds that we deduced so far??
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prove spectral equivalence bounds for inverse fractional power of matrices
ok, so I still have one question: in our case, $A$ and $B$ have eigenvalues in (0,\infty ). so the eigenvalues of $-A$ and $-B$ are in (-\infty ,0) and for $-A^{-1}$ and $-B^{-1}$ they are in in (-\infty ,0) and (-\infty ,0). How can I now deduce the statement using Proposition 2.2 since there it is neccessary to have the eigenvalues in the range $(-1,0)$ ?
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prove spectral equivalence bounds for inverse fractional power of matrices
Thank you for the hint. I have seen that remark, but in proposition 2.2 (to which they refer in that remark) they state that in that case, the eigenvalues of both A and D have to be in (-1,0). In our case, due to positive definiteness of A and D, this does obviously not hold. So the statement does not hold?
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prove spectral equivalence bounds for fractional power of matrices
Thank you - again - for the very profound answer. I have never heard of this theorem before but obviously, it was exactly what I was looking for!
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