A Neural Network for Constrained Saddle Point Problems: An Approximation Approach

摘要

This paper proposes a neural network for saddle point prob-lems(SPP) by an approximation approach. It first proves both the exis-tence 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.