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| 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 |
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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.
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Received: 07 August 2006
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2007, Vol. 29 
