A New Algorithm Based on the Improved Transient Chaotic Neural Network for Cellular Channel Assignment
一种基于改进暂态混沌神经网络的信道分配算法

In this paper,the Transient Chaotic Neural Network(TCNN)is used to solve the Channel Assignment Problem(CAP),and a new method named two-stage annealing method in TCNN is proposed.The neural network gradually convergences,through the transient chaos,to a stable eqnilibrium point according to the damping of the self-feedback connection weight,and the dividing point in the new model is chosen according to the change of the corresponding Lyapunov exponent.The two-stage annealing method can make sure the network take good advantage of the chaos to search the global minimum and enhance the convergence rate.In the 7-cell cellular network,the convergence rate is 30% higher than the TCNN model,and is also upgraded 15% in the Kunz's benchmark test.Simulated results show that the new model has a higher searching ability and lower computing time in searching the global minimum.The searching ability and the choosing of the parameters are also discussed based on the simulated results.