ITERATIVE METHODS FOR SYSTEMS OF EQUATIONS AND UNCONSTRAINED OPTIMIZATION

Credit Hours: 3 · Undergraduate Upper-Level

Iterative methods for linear systems of equations including Krylov subspace methods, including the conjugate gradient method and GMRES; gradient and Newton-like methods for unconstrained optimization and nonlinear least squares problems; Newton and Newton-like methods for nonlinear systems of equations; techniques for improving the global convergence of these algorithms; implementation of these methods in Matlab or Python; applications to example problems in science and engineering. Graduate/Undergraduate Equivalency: CMOR 530 . Recommended Prerequisite(s): (CAAM 453 or CMOR 422 )