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Spectral Gaussian peak feature extraction algorithm based on genetic algorithm

A genetic algorithm and feature extraction technology, applied in the field of spectroscopy, can solve problems such as large fitting errors, poor resolution of aliasing peaks, and inaccurate positioning of Gaussian peaks

Active Publication Date: 2019-01-04
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the shortcomings of inaccurate Gaussian peak positioning, poor resolution of aliasing peaks in the spectrum, and large fitting errors in the prior art, the present invention provides a Gaussian peak feature extraction algorithm based on a genetic algorithm

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  • Spectral Gaussian peak feature extraction algorithm based on genetic algorithm
  • Spectral Gaussian peak feature extraction algorithm based on genetic algorithm
  • Spectral Gaussian peak feature extraction algorithm based on genetic algorithm

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Embodiment Construction

[0068] The accompanying drawings are for illustrative purposes only and cannot be construed as limiting the patent;

[0069] In order to better illustrate this embodiment, some parts in the drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0070] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings.

[0071] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0072] Such as figure 1 As shown, in this example, the TAS7400 terahertz spectrometer produced by Japan Advantech was used to test the castor sugar tablet. The main steps include:

[0073] S1: Obtain the spectral curve y of the caster sugar tablet, and perform curve smoothing and baseline correction on the spectral curve y to obtain the spectral curve z, which specifically includes the follow...

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Abstract

The invention provides a spectrum Gaussian peak feature extraction algorithm based on a genetic algorithm. The main steps include: S1: inputting a spectrum curve, smoothing the spectrum curve and correcting the baseline; S2: population initialization stage; S3: individual variation stage; S4: population crossing stage; S5: population gene decoding stage; 6, calculating fitness fit; 7, judging whether the fitness fit meets the preset condition: if so, executing step S9; if not, executing step S8; S8: natural selection stage; S9: Gaussian peak characteristics being obtained and output by fittingusing the best fitting interval. The invention divides the spectral curve into a plurality of sub-intervals by taking a wave trough as a dividing point, and then combines the sub-intervals to carry out Gaussian peak fitting, obtains an optimal fitting interval through a genetic algorithm, reduces the fitting error, and improves the accuracy of Gaussian peak parameter extraction and the recognition rate of terahertz time domain spectral material identification. The best fitting Gaussian peak number is obtained by the optimization condition of peak number increment, which enhances the resolvingpower of spectral aliasing peaks.

Description

technical field [0001] The present invention relates to the field of spectroscopy, and more specifically, to a Gaussian peak feature extraction algorithm for terahertz spectroscopy based on a genetic algorithm. Background technique [0002] At present, the Gaussian multi-peak fitting algorithm is the most commonly used algorithm for fitting spectral curves. The algorithm first determines the approximate position and number of Gaussian peaks through a monotonic peak-finding algorithm, and then minimizes the fitted curve through a nonlinear iterative optimization algorithm. and the difference between the spectral curve. This algorithm determines the basic information of Gaussian peaks based on the results of monotonic peak-finding, which leads to inaccurate positioning of Gaussian peaks, and ignores the relationship between absorption peaks, and cannot effectively separate the aliasing peaks in the spectrum. Big. [0003] Terahertz time-domain spectroscopy is a very effectiv...

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Application Information

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IPC IPC(8): G06K9/00G06N3/12
CPCG06N3/126G06F2218/08
Inventor 程良伦何伟健梁广宇李学识
Owner GUANGDONG UNIV OF TECH
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