I was thinking of the problem differently -
find the extremal points of
x†Dx, which leads to the eigenvalue
equation Dx = 0. This equation doesn't determine
x†x completely, so one is free to impose, for example, x†x = 1 as a
normalization condition. But you're right that if
x†x = 1 is intended as a true constraint, then a method like Lagrange multipliers should be used.
in reply to Re^2: Help with Matrix math!
in thread Help with Matrix math!