Comment #14 on issue 2225 by mrock...@gmail.com: Enhancing Matrix Norm
http://code.google.com/p/sympy/issues/detail?id=2225

I e-mailed this to the list, it doesn't appear to be coming up. I apologize if a repeat post happens.

Example:
Spectral norm of a matrix (standard 2-norm) can be defined as the largest singular value of that matrix. This is the maximum amount that the matrix can "grow" the 2-norm of a vector.

We can define the principal singular value of a matrix A as the square root of the largest eigenvalue of (A.T * A) (real).

We have symbolic methods to compute eigenvalues (you learned them briefly in high school) so this is alright so far.

The issue I'm having is that I need to return the largest of the eigenvalues and I don't know apriori which that is if things are symbollic. Ideally (I think) I'd return some sort of "Max" object like how we deal with Adds and Pows.

consider A = Matrix([[1 0], [0, x]])
norm(A) == max(1,x) #I'm not sure which it should be yet. We can decide once we have a value for x.

sherjilo... you're right that they end up coming out as very complicated expressions. For even very simple matrices they're often hideous.

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