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We have $N$ Hermitian matrices $A_i$ and $N$ weight values $w_i$, $1\leq i\leq N$, $\sum_{i=1}^N w_i=1$.

Then we can obtain a new Hermite matrices $\sum_{i=1}^N w_iA_i$. let us assume $\lambda$ is the minmum non-zero eigenvalue of $\sum_{i=1}^N w_iA_i$, and vector $X$ is the corresponding eigenvector.

My question is how to select $w_i$, so that $\max_iX^HA_iX$-$\min_iX^HA_iX$ is as minimal as possible.

thanks for your answer.

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I guess you mean Hermitian matrices? –  Suvrit Aug 28 '12 at 16:46
    
Sorry, its a mistake, $A_i$ is a Hermitian matrix. Thank you. –  leslie Aug 29 '12 at 7:17

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