title: Filter design for molecular factor computing using wavelet functions.
abstract: Molecular factor computing (MFC) is a new strategy that employs chemometric methods in an optical instrument to obtain analytical results directly using an appropriate filter without data processing. In the present contribution, a method for designing an MFC filter using wavelet functions was proposed for spectroscopic analysis. In this method, the MFC filter is designed as a linear combination of a set of wavelet functions. A multiple linear regression model relating the concentration to the wavelet coefficients is constructed, so that the wavelet coefficients are obtained by projecting the spectra onto the selected wavelet functions. These wavelet functions are selected by optimizing the model using a genetic algorithm (GA). Once the MFC filter is obtained, the concentration of a sample can be calculated directly by projecting the spectrum onto the filter. With three NIR datasets of corn, wheat and blood, it was shown that the performance of the designed filter is better than that of the optimized partial least squares models, and commonly used signal processing methods, such as background correction and variable selection, were not needed. More importantly, the designed filter can be used as an MFC filter in designing MFC-based instruments.
authors.affiliation: Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Medicinal Chemical Biology, and Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China.
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Li
authors.affiliation: Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Medicinal Chemical Biology, and Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China.
authors.forename: Zhihong
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Medicinal Chemical Biology, and Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China.
authors.forename: Wensheng
authors.initials: W
authors.lastname: Cai
authors.affiliation: Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Medicinal Chemical Biology, and Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China. Electronic address: xshao@nankai.edu.cn.
authors.forename: Xueguang
authors.initials: X
authors.lastname: Shao
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008962:Models, Theoretical; D044967:Serum / Q000737:chemistry; D019265:Spectroscopy, Near-Infrared; D014908:Triticum / Q000737:chemistry / Q000378:metabolism; D003313:Zea mays / Q000737:chemistry / Q000378:metabolism
keywords: Genetic algorithm; Molecular factor computing; Multivariate optical computing; Near-infrared spectroscopy; Wavelet filter