can you help me in this problem

Write a program that generates a number of symmetric matrices with dimensions of 5 by 5 (Marties B) and write a CVX code that finds x where the largest eigenvalue G (x) is minimized.

I will assume the matrices are positive semidefinite; otherwise, the problem is non-convex and can’t be handled by CVX. Let `n`

be the num,ber of matrices.

declare the matrices as

variable B(5,5,n) semidefinite

To minimize the max eigenvalue of `B(:,:,i`

, the objective is

`minimize(lambda_max(B(:,:,i)))`

I will leave it to you how this all comes together in oneCVX program, because I have no idea what your overall objective or constraints are.