Semi-supervised chemometric methodology for improved multivariate calibration of spectrometers.
In this work, a semi-supervised chemometric methodology is designed to improve the predicted accuracy for the multivariate calibration in spectrometers. The simulation is carried out on MATLAB platform. The available toolbox of partial least-squares regression (PLS), which is a very powerful algorit...
محفوظ في:
المؤلف الرئيسي: | Chen, Zheng Yu. |
---|---|
مؤلفون آخرون: | School of Chemical and Biomedical Engineering |
التنسيق: | Final Year Project |
اللغة: | English |
منشور في: |
2010
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://hdl.handle.net/10356/39522 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Chemometric techniques for multivariate calibration and their application in spectroscopic sensors
بواسطة: Ke, Wang
منشور في: (2012) -
Combining multiple models to improve calibration accuracy of spectrometers
بواسطة: Tan, Jonathan Jun Wei.
منشور في: (2010) -
Spectral renormalization for multi-component fourier transform infrared absorbance data: Importance to multivariate calibration and quantitative exploratory chemometrics studies
بواسطة: Chew, W., وآخرون
منشور في: (2014) -
Improving detection of chromosomal abnormalities in multiple myeloma using fluorescence in situ hybridization
بواسطة: Naw, Wah Wah
منشور في: (2010) -
NIR “matchbox size” spectrometer can quantify and detect malaria infection in Plasmodium falciparum infected red blood cells
بواسطة: Adegoke, John A., وآخرون
منشور في: (2020)