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Infrared spectrum wavelength selection method based on integrated L1 regularization

A technology of wavelength selection and infrared spectroscopy, which is applied in the field of infrared spectroscopy, can solve problems such as poor stability, and achieve the effects of strong stability, improved stability, and fewer adjustable parameters

Active Publication Date: 2016-03-02
ZHONGBEI UNIV
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Problems solved by technology

[0005] Aiming at the poor stability of the existing infrared spectrum wavelength selection methods, a new integrated wavelength selection method is proposed. This method first uses the Bootstrap sampling method to generate several sub-datasets for the original data set, and then uses the uninformative The variable elimination method (UninformativeVariableElimination, UVE) preprocesses each sub-dataset, then uses the L1 regularization method to perform feature selection on each sub-dataset, and finally integrates the wavelength selection results of each sub-dataset

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  • Infrared spectrum wavelength selection method based on integrated L1 regularization
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  • Infrared spectrum wavelength selection method based on integrated L1 regularization

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Embodiment Construction

[0034] The following embodiments will further describe the present invention in conjunction with the accompanying drawings.

[0035] Such as figure 1 As shown, it is a system block diagram of the infrared spectrum wavelength selection method based on integrated L1 regularization of the present invention.

[0036] Assuming that there are N samples, the infrared spectrum signal scanned by the spectrometer is The corresponding content of the components to be analyzed is Among them, P is the number of wavelength points in the infrared spectrum, and generally N<<P.

[0037] According to the principle of chemometrics, the content prediction model of the components to be analyzed can be expressed as

[0038] Y=Xb+ε(1)

[0039] in, is the regression coefficient to be fitted; is the noise error.

[0040] First, use the Bootstrap sampling method to resample the original data set with replacement to generate M sub-data sets S 1 ,S 2 ,...,S M , each sub-dataset still contain...

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Abstract

The invention relates to the technical field of infrared spectra, in particular to an infrared spectrum wavelength selection method based on integrated L1 regularization, and the infrared spectrum wavelength selection method uses the integrated learning thought; the infrared spectrum wavelength selection method based on integrated L1 regularization comprises the steps that firstly, a plurality of sub data sets are generated with a Bootstrap sampling method, then each sub data set is subjected to feature selection with an L1 regularization method, a feature selection problem is converted into a sparse optimization problem and then calculation is performed, and finally, wavelength selection results of each sub data set are integrated with a voting method, so that an optimal feature wavelength combination is screened; the infrared spectrum wavelength selection method based on integrated L1 regularization is mainly applied in the infrared spectrum aspect.

Description

technical field [0001] The present invention relates to the technical field of infrared spectroscopy, and more specifically, relates to an infrared spectrum wavelength selection method based on integrated L1 regularization, which is an infrared spectrum wavelength selection method using the idea of ​​integrated learning. Background technique [0002] Infrared spectroscopic analysis is a new analytical technique, which has been widely used in the fields of agriculture, chemical industry and environmental monitoring due to its advantages of fast, non-destructive and non-polluting. However, infrared spectroscopy usually has the characteristics of multiple wavelength points, overlapping absorption peaks, and serious collinear relationship between wavelength points, which makes subsequent qualitative and quantitative analysis difficult. Therefore, the study of wavelength selection methods has important practical significance for simplifying the model and improving the predictive ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/35G01N21/359
CPCG01N21/35G01N21/359
Inventor 陈媛媛景宁李墅娜张瑞李晋华王芳吕润发李珊刘璐王志斌
Owner ZHONGBEI UNIV
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