期刊文献+

用一种少参数非线性自适应滤波器自适应预测低维混沌时间序列 被引量:21

NONLINEAR ADAPTIVE PREDICTION OF CHAOTIC TIME SERIES WITH A REDUCED PARAMETER NONLINEAR ADAPTIVE FILTER
原文传递
导出
摘要 基于混沌动力系统的相空间延迟坐标重构 ,利用混沌序列固有的确定性和非线性 ,提出了用于混沌时间序列预测的一种少参数非线性自适应滤波预测模型 .该预测模型在Volterra自适应滤波器的基础上引入sigmoid函数来减少待定参数 .实验研究表明 ,这种少参数非线性自适应滤波预测器仅需用 5 0个样本经 2 0次预训练后 ,就能有效地预测一些低维混沌序列 ,且这种少参数非线性自适应滤波预测器更便于工程实现 . Based on the deterministic and nonlinear characterization of the chaotic signals, a new reduced parameter nonlinear adaptive filter is proposed to make adaptive predictions of chaotic time series. The sigmoid function is introduced to nonlinear predictive filter for reducing unknown parameters of the second order Volterra filters. A reduced parameter nonlinear adaptive filtering prediction scheme is suggested in order to track current chaotic trajectory by using precedent predictive error for adjusting filter parameters rather than approximating global or local map of chaotic series. Experimental results show that this reduced parameter nonlinear adaptive filter, which is only trained with 50 samples and 20 iterations, can be successfully used to make one step and multi step predictions of chaotic time series.
出处 《物理学报》 SCIE EI CAS CSCD 北大核心 2000年第12期2333-2339,共7页 Acta Physica Sinica
基金 国防预研基金!(批准号 :98JS0 5 .4.1.DZ0 2 0 5 )资助的课题&&
关键词 少参数非线性自适应滤波器 混沌时间序列 chaos, nonlinear adaptive prediction, reduced parameter nonlinear filter, adaptive algorithms
  • 引文网络
  • 相关文献

参考文献2

二级参考文献4

共引文献176

同被引文献151

引证文献21

二级引证文献235

;
使用帮助 返回顶部