摘要
基于混沌动力系统相空间的延迟坐标重构和双线性表达式,设计了预测混沌时间序列的双线性自适应预测滤波器.对2种低维混沌序列的预测实验表明,采用双线性自适应滤波器的预测收敛速度快,处理约50个样本时即已收敛,预测相对误差小于0.001.
Based on the delay-coordinate reconstruction and bilinear expressions in the phase space of a chaotic system, a bilinear adaptive filter was designed to predict low-dimensional chaotic time series. Experiments conducted on two examples of low-dimensional chaotic series show that, using the bilinear adaptive filter, the prediction process converges after about 50 samples are processed and the relative prediction error is less than 0.001.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2004年第4期490-493,共4页
Journal of Southwest Jiaotong University
基金
国家自然科学基金资助项目(60272096)西南交通大学基础科学研究基金的资助 (2 0 0 1B0 8)