A versatile strategy for achieving the second-order advantage when applying different artificial neural networks to non-linear second-order data: Unfolded principal component analysis/residual bilinearization

Chemometrics and Intelligent Laboratory Systems

Volumn 92, Issue 1, 2008, Pages 61-70

  García Reiriz, Alejandro ^a   Damiani, Patricia C ^a   Culzoni, María J ^b   Goicoechea, Héctor C ^b   Olivieri, Alejandro C ^a  

^a UNIVERSIDAD NACIONAL DE ROSARIO   (Argentina)

^b UNIVERSIDAD NACIONAL DEL LITORAL   (Argentina)

Author keywords

Multilayer perceptron networks; Radial basis functions; Residual bilinearization; Second order advantage; Support vector machines

Indexed keywords

AMOXICILLIN; POLYCYCLIC AROMATIC HYDROCARBON; SALICYLIC ACID;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL COMPOSITION; DRUG DETERMINATION; FIELD EMISSION; NONLINEAR SYSTEM; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIGNAL DETECTION; SUPPORT VECTOR MACHINE; ULTRAVIOLET RADIATION;

EID: 43049155941     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.chemolab.2007.12.002     Document Type: Article

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