  Scaling frame vectors is a simple and noninvasive way to construct tight
frames. However, not all frames can be modifed to tight frames in this fashion,
so in this case we explore the problem of finding the best conditioned frame by
scaling, which is crucial for applications like signal processing. We conclude
that this problem is equivalent to solving a convex optimization problem
involving the operator norm, which is unconventional since this problem was
only studied in the perspective of Frobenious norm before. We also further
study the Frobenious norm case in relation to the condition number of the frame
operator, and the convexity of optimal scalings.
