Applying Wavelet Frequency Component Correlative Selection in Raman Spectral Analysis

摘要：

To overcome the limitations of existing wavelet transform (WT) preprocessing methods for Raman spectra, an improved preprocessing method -WT frequency component correlative selection algorithm -is proposed. Raman spectra are firstly prism-decomposed by WT, then correlations between every frequent weight and target are computed and threshold is set to select the efficient input data for calibration model. Applying this method in gasoline Raman spectra data preprocessing, experimental results show the new algorithm obviously weaken the fluorescence and high frequent noise and improves the prediction performance of the partial least square (PLS) model for gasoline octane number comparing with other existing methods.

关键词： Wavelet Transform Meyer wavelet spectral analysis partial least square

作者: Guijun Yang

作者单位: Hangzhou Institute Of Commerce Zhejiang Gongshang University Hangzhou 310018, China

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 321-324

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）