CONVERGENCE ANALYSIS ON MINIMAX NEURAL NETWORKS

YE Zhongquan, ZHANG Bangli, CAO Changxiu. CONVERGENCE ANALYSIS ON MINIMAX NEURAL NETWORKS[J]. INFORMATION AND CONTROL, 1997, 26(1): 1-6.

Citation:

YE Zhongquan, ZHANG Bangli, CAO Changxiu. CONVERGENCE ANALYSIS ON MINIMAX NEURAL NETWORKS[J]. INFORMATION AND CONTROL, 1997, 26(1): 1-6.

Citation:

YE Zhongquan, ZHANG Bangli, CAO Changxiu. CONVERGENCE ANALYSIS ON MINIMAX NEURAL NETWORKS[J]. INFORMATION AND CONTROL, 1997, 26(1): 1-6.

Abstract

The study of the minimax problem is of important significance for the game theory,mathematical programming and optimal control,and numerical methods of solving these problems are needed in a wide class of applications.In this paper we construct a neural network of continuous-time dynamical system to explore the minimax problem.The stability and convergence of the network are investigated by using Lyapunov function under suitable conditions.We have also proved that the equilibrium points of the network are the saddle points of the problem.

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