scispace - formally typeset
Journal ArticleDOI

Calibration transfer of near‐infrared spectra for extraction of informative components from spectra with canonical correlation analysis

Reads0
Chats0
TLDR
In this paper, a new calibration transfer method that applies canonical correlation analysis (CCA) to transfer the informative components extracted from a spectral dataset is proposed to reduce the interference of noise, background and non-predicted properties.
Abstract
A new calibration transfer method that applies canonical correlation analysis (CCA) to transfer the informative components extracted from a spectral dataset is proposed to reduce the interference of noise, background and non-predicted properties. This method employs the partial least squares method to extract the informative components related to the predicted properties from the raw spectra and then corrects the informative components based on CCA. The performance of this algorithm was tested using three pairs of spectra batches: two pairs of corn spectra and one pair of tri-component solvent spectra. The results showed that this method can significantly reduce prediction errors compared with CCA and piecewise direct standardization. Copyright © 2014 John Wiley & Sons, Ltd.

read more

Citations
More filters
Journal ArticleDOI

Near infrared spectroscopy: A mature analytical technique with new perspectives - A review.

TL;DR: Last decade's advances and modern aspects of near infrared spectroscopy are critically examined and reviewed in order to understand why the technique has found intensive application in the most diverse and modern areas of analytical importance during the last ten years.
Journal ArticleDOI

Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples

TL;DR: A method named as linear model correction (LMC) is proposed for calibration transfer without standard samples based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated.
Journal ArticleDOI

Correcting multivariate calibration model for near infrared spectral analysis without using standard samples

TL;DR: In this article, a partial least squares (PLS) model was constructed using the calibration spectra measured with a primary instrument, and the model was then used to predict the spectra from a secondary instrument.
Journal ArticleDOI

Calibration transfer of near-infrared spectroscopy by canonical correlation analysis coupled with wavelet transform.

TL;DR: WTCCA is a promising calibration transfer method which can be recommended for on-line/in-line application and yielded the lowest root mean standard error of prediction (RMSEP) on the three analytes in three physical states.
Journal ArticleDOI

Calibration transfer based on the weight matrix (CTWM) of PLS for near infrared (NIR) spectral analysis

TL;DR: In this paper, two new calibration transfer methods based on the weight matrix (CTWM) of partial least squares (PLS) were proposed, which can be applied to the occasion when both the primary and secondary spectra of standardization samples can be obtained.
References
More filters
Journal ArticleDOI

Partial least-squares regression: a tutorial

TL;DR: In this paper, a tutorial on the Partial Least Squares (PLS) regression method is provided, and an algorithm for a predictive PLS and some practical hints for its use are given.
Journal ArticleDOI

Computer Aided Design of Experiments

TL;DR: A computer oriented method which assists in the construction of response surface type experimental plans takes into account constraints met in practice that standard procedures do not consider explicitly.
Journal ArticleDOI

Analysis of water in food by near infrared spectroscopy

TL;DR: The analysis of water by near infrared spectroscopy (NIRS) was the first successful application of this rapid technology which has developed over the past 30 years into a routine method for many agricultural commodities and food constituents.
Journal ArticleDOI

Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram

TL;DR: A new method for muscle artifact removal in EEG is presented, based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique, which outperformed a low-pass filter with different cutoff frequencies and an independent component analysis (ICA)-based technique for muscle artifacts removal.
Related Papers (5)