摘要
提出了利用前馈神经网络预测联合混沌序列,通过引用著名的Henon和Lozi混沌系统作为仿真实验产生联合混沌信号序列。预测结果证明,用改进的BP算法训练的NN可以完全预测联合混沌信号序列。
The combined chaotic time series is predicted by using the standard feed-forward neural networks (NN). Henon and Lozi systems are used to generate the combined chaotic time series. From the forecasting results, it can be concluded that the NN, which is trained by improved back-propagation (BP) algorithms, can be well applicable for combined chaotic time series prediction.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2004年第10期1225-1228,1233,共5页
Journal of Optoelectronics·Laser
基金
SupportedbyNationalNaturalScienceFoundationofChina(60 1 740 2 1 )
KeyProjectofTianjinNaturalScienceFoundation(0 1 380 0 71 1 )
