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Artificial neural networks Characterization and identification of edible oil blends and prediction of the composition by artificial neural networks -A case study 117 Atomic absorption spectrometry Application of the response surface methodology for potassium determination in soils by AAS using the slurry technique 239 Calibration Application of latent root regression for calibration in near-infrared spectroscopy. Comparison with principal component regression and partial least squares 231 Characteristics identification Correlative components analysis for pattern classification 221 Chromatography Criteria for optimizing the separation of target analytes in complex chromatograms 67 Classification Recent developments in discriminant analysis on high dimensional spectral data 157 Reduction of the size of the learning data in a probabilistic neural network by hierarchical clustering. Application to the discrimination of seeds by artificial vision 175 Color image analysis Reduction of the size of the learning data in a probabilistic neural network by hierarchical clustering. Application to the discrimination of seeds by artificial vision 175 Correlative components Correlative components analysis for pattern classification 221 Critical components Correlative components analysis for pattern classification 221 Data pretreatment Artificial neural networks in classification of NIR spectral data: Selection of the input 127 Dimensionality reduction Artificial neural networks in classification of NIR spectral data: Selection of the input 127 Dimension reduction Recent developments in discriminant analysis on high dimensional spectral data 157 Discriminant analysis Recent developments in discriminant analysis on high dimensional spectral data 157 D-optimal Genetic algorithm as a tool for selection of D-optimal design 105
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