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Spectrogram abnormal sample point detection method based on random sampling agree set

A random sampling and detection method technology, applied in the direction of color/spectral characteristic measurement, etc.

Inactive Publication Date: 2013-04-03
江苏易谱恒科技有限公司
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Problems solved by technology

Various complex situations in practical applications, such as observation conditions, operational factors, etc., will lead to the appearance of abnormal sample points

Method used

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  • Spectrogram abnormal sample point detection method based on random sampling agree set
  • Spectrogram abnormal sample point detection method based on random sampling agree set
  • Spectrogram abnormal sample point detection method based on random sampling agree set

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Embodiment Construction

[0044] Below in conjunction with accompanying drawing, the present invention will be described in further detail:

[0045] Such as figure 1 As shown, the present invention has designed a kind of spectrogram abnormal sample point detection method based on random sampling consistent set, comprises following specific steps:

[0046] Step (1): Perform robust principal component analysis on the given spectral data X, detect and eliminate abnormal spectral sample points, and obtain the corrected sample set X c , record the calibration sample set X c The number of samples in the middle is m c ;

[0047] Step (2): The calibration sample set X in the step (1) c Random sampling is performed to obtain the current training set X s ;

[0048] Step (3): Based on the training set X in the step (2) s Establish a multivariate calibration model and calculate the model prediction residual error E s ;

[0049] Step (4): Using the multivariate correction model and model in step (3) to pre...

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Abstract

The invention discloses a spectrogram abnormal sample point detection method based on a random sampling agree set. The spectrogram abnormal sample point detection method comprises the following steps of: eliminating part of an abnormal sample in advance so as to obtain a correcting sample set through principal component analysis on the base of a maximum posteriori probability random sampling agree set and starting from a given spectroscopic data, carrying out random sampling, establishing multivariated correcting model and evaluating a model property, and selecting an appropriate sample subset as an inner point set through random sampling for many times. The designed spectrogram abnormal sample point detection method based on the random sampling agree set, provided by the invention, has the advantages of being rapid, effective, high in accuracy and wide in application range.

Description

technical field [0001] The invention relates to the technical field of data processing of multivariate calibration models of chemometrics, in particular to a method for detecting abnormal sample points of spectrograms based on random sampling consistent sets. Background technique [0002] With the development of modern analytical instruments, the detection signal has changed from a traditional single value to a complete spectrum, even an image. For spectral data, the dimensionality is usually very high relative to the number of samples collected. At this time, the correction regression problem is seriously ill-conditioned. The traditional one-variable correction method is difficult to analyze these data, and the multivariate correction method is used instead. [1] . Chemometrics multivariate correction technology directly uses the measurement signal, and establishes a quantitative model between the spectral signal and the sample concentration through dimensionality reduction...

Claims

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Application Information

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IPC IPC(8): G01N21/25
Inventor 王海燕刘军姜久英
Owner 江苏易谱恒科技有限公司
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