No abstract

No abstract

No abstract

The formulation of the transfer function identification problem leads directly to a nonlinear optimization problem. This nonlinear optimization problem is nonconvex and may exibit many local optima. As a result of the presence of local optimum, optimization methods based upon gradient techniques cannot be guaranteed to converge to the Global Optimum. A relaxation branch and bound technique is proposed to solve the problem. The algorithm will be presented and its convergence prop erties discussed. In addition several simulation examples utilizing the global technique are provided.