论文部分内容阅读
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 type of curve fitting technique, Spline Wavelet Least Squares (S W L S), is applied to the processing of analytical chemical signals. As a new technique to filter noise, the influences of various filtering parameters on the filtering results are discussed in detail. If proper parameters are selected, the useful information can be extracted from the high noise with S / N = 0.5, and the error of the peak current is less than 3% and the error of the peak potential is less than 10%. Compared with wavelet multi-frequency channel filtering (W M C D) and spline least square method (S L S), it is found that this method can solve some problems existing in W M C D and S L S. The experimental data of D P S V and X-ray photoelectron spectroscopy were applied to validate this method. Satisfactory results were obtained.