%0 Journal Article
%T A novel subband forecast method for nonlinear time series using wavelet transform<br>非线性时间序列的小波分频预测
%A Lei Ming
%A Han Chong-Zhao
%A Guo Wen-Yan
%A Wen Xiao-Qin
%A <br>雷 明
%A 韩崇昭
%A 郭文艳
%A 文小琴
%J 物理学报
%D 2005
%I 
%X In this paper, a new method is proposed to implement subband forecast within the nonlinear noisy time series based on abstracting and reconstruction of the sign al's main components and adaptive Volterra filter theory.By considering noise's wavelet transform characteristic,the main component of noise signal is abstracte d by using the wavelet package decomposition in an appropriate scale and the ma ximum module reconstruction algorithm,then the forecast components are brought f rom adaptive Volterra forecast filter to reconstruction the final signal.This m ethod improves the traditional blindness in selecting scale in wavelet decomposi ng denoise,avoids the shortage of antinoise capability of Volterra series model used singly.The simulated results show that it is a practicable and effective me thod for nonlinear noise signal.
%K wavelet decompose
%K Volterra adaptive filter
%K sub-band forecast<br>小波分解
%K Volterra自适应滤波器
%K 分频预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=C5BC1358C4A65983&yid=2DD7160C83D0ACED&vid=318E4CC20AED4940&iid=94C357A881DFC066&sid=0702FE8EC3581E51&eid=D418FDC97F7C2EBA&journal_id=1000-3290&journal_name=物理学报&referenced_num=4&reference_num=13