کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9745493 | 1491573 | 2005 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discriminating from highly multivariate data by Focal Eigen Function discriminant analysis; application to NIR spectra
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Discriminating between classes from spectra deals with an ill-conditioned problem, which is generally solved by means of dimension reduction, using principal component analysis or partial least squares regression. In this paper, a new method is presented, which aims at finding a parcimonious set of discriminant vectors, without reducing the dimension of the space. It acts by scanning a restricted number of scalar functions, called Focal Eigen Functions. These functions are theoretically defined and some of their interesting properties are proven. Three scanning algorithms, based on these properties, are given as examples. An application to real spectroscopic data shows the efficiency of that new method, compared to the Partial Least Squares Discriminant Analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 79, Issues 1â2, 28 October 2005, Pages 31-41
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 79, Issues 1â2, 28 October 2005, Pages 31-41
نویسندگان
J.M. Roger, B. Palagos, S. Guillaume, V. Bellon-Maurel,