Neural network for global optimization
全局优化的神经网络方法

A neural network model for solving global optimization problems is proposed. The convergence and feasibility of the model are analyzed. Then an algorithm is provided. It is strictly proved that for an arbitrarily given initial point of an optimization problem, the algorithm converges to a global minimizer of the problem. Finally, simulation results are presented to \{illustrate\} the effectiveness of the algorithm.