Novel method to solve TSP by continuous Hopfield neural network
基于连续Hopfield网络求解TSP的新方法

Whether both continuous Hopfield neural network (CHNN) and its energy function have self-feedback or not,it is called uniform CHNN.Firstly,convergence of uniform CHNN is analyzed.Secondly,the character of energy function variation are studied when the CHNN has self-feedback while its energy function has not self-feedback.Thirdly, conditions are proposed to ensure that the energy function can increase,decrease or not change respectively.This principle eradicates local minima or invalid solutions caused by consistent reduction of the energy function via the usual gradient descent method.Furthermore,a new approach to solve TSP (traveling salesman problem) is proposed according to this principle.Finally,simulations show the new approach can provide very good results when it is used to solve TSP.