A New Algorithm Based on the Improved Transient Chaotic Neural Network for Cellular Channel Assignment
Zhu Xiao-jin; Chen Yan-chun; Ma Shi-wei; Qin Ting-gao
School of ElectroMechanical Engineering & Automation Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai 200072, China
Abstract：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 equilibrium 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.
2007, Vol. 29 
