Determining the contents of fat and protein in milk powder by using near infrared spectroscopycombined with wavelet transform and radical basis function neural networks

Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves

Volumn 29, Issue 2, 2010, Pages 128-131

  Shan, Yang ^a,b   Zhu, Xiang Rong ^b   Xu, Qing Song ^a   Liang, Yi Zeng ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b Hunan Food Test and Analysis Center   (China)

Author keywords

Kernard Stone algorithm; Milk powder; Near infrared (NIR) spectroscopy; Radical basis function neural networks; Wavelet transformation

Indexed keywords

CHEMOMETRIC METHOD; CORRECTION MODELS; CORRELATION COEFFICIENT; DE-NOISING; DECOMPOSITION LEVEL; MILK POWDER; NEAR INFRARED; PREDICTION ACCURACY; PREDICTION MODEL; RADICAL BASIS FUNCTION NEURAL NETWORKS; RBF NETWORK; ROOT MEAN SQUARE ERRORS; SPECTRAL SIGNAL; THREE PARAMETERS; WAVELET FUNCTION; WAVELET TRANSFORMATION; WAVELET TRANSFORMATIONS;

ALGORITHMS; CHROMATOGRAPHY; ERROR CORRECTION; FORECASTING; INFRARED DEVICES; INFRARED SPECTROSCOPY; MATHEMATICAL MODELS; PROTEINS; WAVELET DECOMPOSITION;

NEURAL NETWORKS;

EID: 77952600266     PISSN: 10019014     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1010.2010.00128     Document Type: Article

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