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April 6th, 2016, 09:18 AM   #1
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Proof concerning eigenvalue and matrix norm.

Hi, I am struggling with the following proof. I think I know how to prove the right hand side inequality |lambda| <= ||A||, but I still don't know how to prove the left hand side inequality.

Could you please give me some hint ?
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hegendroffer is offline  
May 22nd, 2016, 02:08 AM   #2
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Hey hegendroffer.

Hint - Use the sub-multiplicative norm with respect to the eigen-decomposition of the matrix and consider the result of the inverse of the matrix (in terms of how the eigen-values become reciprocated).

The eigen-decomposition should have three matrices of PDP_inverse and the sub-multiplicative law of matrix norms in combination with how eigen-values are determined for the original matrix and the inverse relate to that result.
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June 2nd, 2016, 04:30 AM   #3
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Let ui and $\displaystyle \lambda_{i}$ be eigenvectors and eigenvalues of A
x=x1u1+..xnun, ||x||=1
||Ax||=||$\displaystyle \lambda_{1}$x1u1+...$\displaystyle \lambda_{n}$xnun|| $\displaystyle \geq$ |$\displaystyle \lambda_{1}$|,..,|$\displaystyle \lambda_{n}$|
||A|| $\displaystyle \geq |\lambda|$

Au=$\displaystyle \lambda$ u
A$\displaystyle ^{-1}$u=1/$\displaystyle \lambda$ u
||A$\displaystyle ^{-1}$||$\displaystyle \geq$ 1/|$\displaystyle \lambda$|
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