SCOPUS 정보 검색 플랫폼

Chemometrics and Intelligent Laboratory Systems

Volumn 54, Issue 2, 2000, Pages 93-106

Neural network modelling for very small spectral data sets: Reduction of the spectra and hierarchical approach

(5) Tchistiakov, Valeri a Ruckebusch, Cyril b Duponchel, Ludovic b Huvenne, Jean Pierre b Legrand, Pierre b

a INSTITUTE OF PHYSIOLOGICALLY ACTIVE COMPOUNDS (Russian Federation)

b UNIVERSITÉ DES SCIENCES ET TECHNOLOGIES DE LILLE (France)

Author keywords

Artificial neural networks; FTIR; Infrared spectroscopy; Multilevel modelling; Transformations; Wavelet

Indexed keywords

INDUSTRIAL CHEMICAL; STARCH;

ACCURACY; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; DRUG IDENTIFICATION; FOURIER TRANSFORMATION; INFRARED SPECTROMETRY; MATHEMATICAL MODEL; PAPER; PRIORITY JOURNAL; SPECTROSCOPY; TECHNIQUE;

EID: 0034731526 PISSN: 01697439 EISSN: None Source Type: Journal
DOI: 10.1016/S0169-7439(00)00108-8 Document Type: Article

Times cited : (21)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.