A Method of Infrared Spectrum Wavelength Selection Based on Adaptive Group Lasso

An infrared spectrum and wavelength selection technology, applied in the field of infrared spectrum wavelength, can solve the problems of few adjustable parameters, strong robustness, and small amount of calculation, and achieve the goal of less adjustable parameters, strong robustness, and small amount of calculation Effect

Inactive Publication Date: 2017-07-18
ZHONGBEI UNIV
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Problems solved by technology

[0006] In order to overcome the disadvantages of large amount of calculation and weak robustness existing in the infrared spectrum wavelength selection method in the prior art, the present invention proposes a method based on adaptive Group Lasso with small amount of calculation, few adjustable parameters and strong robustness. Infrared Spectroscopy Wavelength Selection Method

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  • A Method of Infrared Spectrum Wavelength Selection Based on Adaptive Group Lasso
  • A Method of Infrared Spectrum Wavelength Selection Based on Adaptive Group Lasso
  • A Method of Infrared Spectrum Wavelength Selection Based on Adaptive Group Lasso

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[0038] The following embodiments will further describe the present invention in conjunction with the accompanying drawings.

[0039] The following combination figure 1 and figure 2 The present invention is described in detail.

[0040] Such as figure 1 As shown, 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<

[0041] According to the principle of chemometrics, the content prediction model of the components to be analyzed can be expressed as

[0042] Y=Xβ+ε (1)

[0043] in, is the regression coefficient to be fitted; is the noise error.

[0044] To achieve wavelength selection, using convex optimization theory, the problem can be transformed into the following l 1 Norm sparse optimization problem:

[0045]

[0046] From such as figure 2 From the second der...

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Abstract

The invention relates to the technical field of infrared spectrum wavelength, and concretely relates to a convex optimization theory-based novel infrared spectrum wavelength selection method. The method is a self-adaptive wavelength selection method adopting a Group Lasso technology without knowing spectrum partitioning priori knowledge. An infrared spectrum wavelength screening problem is converted into a Group Lasso sparse optimization problem, the sparse structure priori knowledge of the infrared spectrum is fully used to self-adaptively determine the partitioning size, a Shooting rapid algorithm is adopted to calculate the sparse solution, and Belsley colinearity examination of the sparse solution is carried out on the sparse solution to reject wavelength points with small contribution. The method has the advantages of small calculation capacity, few adjustable parameters and strong robustness, can effectively reduce the complexity of a model and improve the generalization performance of the model, and can be widely used in the field of infrared spectrum wavelength selection of a solid phase, a liquid phase and a gas phase.

Description

technical field [0001] The present invention relates to the technical field of infrared spectrum wavelength, and more specifically, relates to a novel infrared spectrum wavelength selection method based on convex optimization theory, which is an adaptive wavelength selection using the Group Lasso method without prior knowledge of spectral block. method. 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 m...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N21/3577G01N21/359
Inventor 陈媛媛李墅娜王志斌张瑞陈友华王芳李克武张敏娟李晋华
Owner ZHONGBEI UNIV
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