中文摘要：

采用MATLAB小波分析方法对PM10质量浓度时间序列数据进行去噪处理,分析了MATLAB小波去噪分析函数具体参数的选择及其对去噪处理效果的影响,结果表明不同参数对小波去噪的效果有不同的影响,应该根据时间序列数据的特点进行选择,以达到较好的去噪效果.对北京市2010-2011年度PM10质量浓度随时间变化的实际数据进行小波去噪分析表明,小波去噪分析能较好地显示PM10的时间变化规律.

英文摘要：

The wavelet analysis based on MATLAB was employed to denoise the PMI~, mass concentration time series data in this paper. The selection of parameters of wavelet de-noising function in MATLAB and its influences on de-noising of PM10 concentration was investigated. The results show that different parameters of wavelet de-noising function influence the wavelet de-noising obviously and should be chosen correctly to a better de-noising result according to the feature of the time series data. The wavelet de-noising of PMI0 mass concen- tration variation during 2010 to 2011 in Beijing suggests that there are some year regularity on PM10 concentra- tion variation of Beijing. The wavelet de noising processing can reveal the time variation regularity of PMI0 ap- parently.