摘要
研究了一种新型的曲线拟合技术———样条小波最小二乘法 （ Ｓ Ｗ Ｌ Ｓ） 在处理分析化学信号中的应用。作为一种滤除噪声的新技术，详细讨论了各种滤波参数对滤波结果的影响。若选择了合适的参数， 就可以从信噪比 Ｓ／ Ｎ＝ ０５ 的高噪声中提取有用信息， 且峰电流的误差小于３０ ％ ， 峰电位的误差小于１０ ％ 。并将之与小波多频率通道滤波法 （ Ｗ Ｍ Ｃ Ｄ） 及样条最小二乘法 （ Ｓ Ｌ Ｓ） 进行了比较， 发现该方法可以解决 Ｗ Ｍ Ｃ Ｄ 及 Ｓ Ｌ Ｓ 中存在的一些问题。并将之应用于 Ｄ Ｐ Ｓ Ｖ 及 Ｘ射线电子能谱实验数据的处理以验证该方法， 取得了满意的结果。
A new curve fitting method\|spline wavelet least square (SWLS) has been applied in processing analytical chemistry signals. As a new technique in signal processing, to extract useful signals from high noise, the influences of different parameters on the results of processing is discussed, including the different mth\|order spline wavelet basis (m); the distance between spline wavelet basis (h) and the signal\|to\|noise ratio (S/N). If the suitable parameters are selected, useful signals can be filtered from the noise of S/N=0.5. The relative errors of peak current are less than 3 0%, and that of peak potential is less than 10%. Comparison of this method with wavelet multifrequency channel decomposition (WMCD) and SLS has also been made and it indicates that SWLS can solve some problems in WMCD and SLS. For testing these methods, the experimental data of Differential Pulse Stripping Voltammetry (DPSV) in the determination of HCHO and X\|ray Photoelectron Spectroscopy (XPS) of nitrogen in carbon fiber are used with satisfactory results.
出处
《计算机与应用化学》
CAS
CSCD
1999年第5期371-372,共2页
Computers and Applied Chemistry
基金
国家自然科学基金
广东省自然科学基金
