The P.I. will attempt to apply current methodology from nonlinear programming to the solution of unconstrained optimization problems arising in applications of neural nets. The four main areas of investigation are: solving large problems using recent developments in conjugate gradient and Newton methods; development of methods for obtaining global as opposed to strictly local solutions; application of sensitivity theory to provide post-optimality analysis; use of factorable function theory to develop varieties of functional forms describing the input-output relations.
