Polynomial optimization using semidefinite programming
Smith, Michael D.
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In this thesis, our goal is to study the problem of minimizing a polynomial p(x) using semidefinite matrices. Our discussion will cover Lagrangian duality and conic programming, followed by a discussion on how nonnegative polynomials can be approximated by sums of squares. We will use this approximation to create our semidefinite programming problems. This will lead us to being able to solve the problem of wireless coverage using minimum transmission.