A neural network for constrained saddle point problems: An approximation approach

Abstract

This paper proposes a neural network for saddle point problems(SPP) by an approximation approach. It first proves both the existence and the convergence property of approximate solutions, and then shows that the proposed network is globally exponentially stable and the solution of (SPP) is approximated. Simulation results are given to demonstrate further the effectiveness of the proposed network. © Springer-Verlag Berlin Heidelberg 2005.