摘要
介绍了一种新型基于相空间重构和返回图法的非线性降噪方法——搜索平均法,首先将该方法应用于被高斯白噪声所污染的Henon映射时间序列,说明根据降噪理论所编写的计算程序的正确性;然后应用于中国气象局公布全国435站1960—2000年的逐日气温观测时间序列,并利用非线性预报方法衡量降噪的效果,验证了该方法的有效性.
The searching average nonlinear noise reduction method, which is based on local linear fit to the nonlinear dynamics, is introduced to reduce the noise in the observation data of climatology. Recurrence plots arc used to estimate the size of local neighbors. The noise reduction is improved markedly. In order to show the validity of the program in noise reduction, it is first applied to a noise time series of Henon map contaminated by Gaussian white noise. And then, this noise reduction scheme is applied separately to the observation data of meteorology. The analyses of a nonlinear prediction demonstrate the efficiency of the method for noise reduction.
出处
《物理学报》
SCIE
EI
CAS
CSCD
北大核心
2007年第1期589-596,共8页
Acta Physica Sinica
基金
国家自然科学基金(批准号:90411008)
国家重点发展基础研究项目(批准号:2006CB400503)资助的课题~~
关键词
返回图法
非线性降噪
非线性预报
recurrence plots, nonlinear noise reduction, nonlinear prediction
