  We study the spectrum reconstruction technique. As is known to all,
eigenvalues play an important role in many research fields and are foundation
to many practical techniques such like PCA(Principal Component Analysis). We
believe that related algorithms should perform better with more accurate
spectrum estimation. There was an approximation formula proposed, however, they
didn't give any proof. In our research, we show why the formula works. And when
both number of features and dimension of space go to infinity, we find the
order of error for the approximation formula, which is related to a constant
$c$-the ratio of dimension of space and number of features.
