Rank of a Hermitian matrix?

5 views (last 30 days)
Muhammad
Muhammad on 18 Sep 2018
Commented: Brendan Hamm on 19 Sep 2018
I have a complex Hermitian matrix, say W, which is obtained by solving a convex optimization problem. In order for this matrix to be the result of my original problem, W must satisfy the following condition rank ( W ) = 1. When I checked this condition, MATLAB gives me an answer 3 for 3x3 W matrix. However, eigenvalues of this matrix are [-2.04e-11,-1.92e-12,2.81]. Now, my question is should I consider W as a rank-1 matrix based on the eigenvalues result or should I consider it as a rank 3 matrix as provided by MATLAB rank condition? (I have learnt that the rank of a symmetric matrix is the number of non-zero eigenvalues. If this is the case, can I also extend this def to Hermitian matrix? and If this def is also true for hermitian matrix, then what should be the rank of W (1 or 3))?
  2 Comments
David Goodmanson
David Goodmanson on 19 Sep 2018
Hi Muhammad,
First, nonzero eigenvalue = rank is true for Hermitian matrices.
You will have to make a judgment call, but in this context it's very likely to be rank 1. For the rank function, the default tolerance for determining zeros in this case is < 1.3e-15. That's a stringent requirement. The more complicated a process you have to calculate W, the larger the allowed tolerance can be on determining zeros. Not knowing the problem makes commenting a bit presumptuous. But generally, 2e-11 seems small enough to be considered zero. If it were, say, 1e-8 I would be suspicious that there was something else going on. Everyone calibrates their own antenna.
Brendan Hamm
Brendan Hamm on 19 Sep 2018
You may also consider changing the tolerance on your constraint in the optimization routine. Look at the doc for optimoptions under the solver you are using.

Sign in to comment.

Answers (0)

Categories

Find more on Sparse Matrices in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!