Neural networks in multivariate calibration

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Nonlinear PLS modeling using neural networks

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Nonlinear multivariate calibration using principal components regression and artificial neural networks

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Optimal minimal neural interpretation of spectra

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Noise suppression and signal compression using the wavelet packet transform

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Influence of Temperature on Vibrational Spectra and Consequences for the Predictive Ability of Multivariate Models

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The Radial Basis Functions — Partial Least Squares approach as a flexible non-linear regression technique

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Spectroscopic calibration and quantitation using artificial neural networks

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Using artificial neural networks for solving chemical problems

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Neural Network Studies. 2. Variable Selection

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PLS/neural networks

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Nonlinear multivariate mapping of chemical data using feed-forward neural networks

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Rapid and Quantitative Analysis of the Pyrolysis Mass Spectra of Complex Binary and Tertiary Mixtures Using Multivariate Calibration and Artificial Neural Networks

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Tutorial review—Data processing by neural networks in quantitative chemical analysis

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Processing of signals from an ion-elective electrode array by a neural network

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Feed-forward artificial neural networks: applications to spectroscopy

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Robustness analysis of radial base function and multi-layered feed-forward neural network models

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Comparison of the training of neural networks for quantitative x-ray fluorescence spectrometry by a genetic algorithm and backward error propagation

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Preprocessing of HPLC Trace Impurity Patterns by Wavelet Packets for Pharmaceutical Fingerprinting Using Artificial Neural Networks

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Data processing using neural networks

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Variable selection for neural networks in multivariate calibration

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Selection of the Best Calibration Sample Subset for Multivariate Regression

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Octane number prediction based on gas chromatographic analysis with non-linear regression techniques

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Characterisation of the representativity of selected sets of samples in multivariate calibration and pattern recognition

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Neural network based recognition of flow injection patterns

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Rugged spectroscopic calibration for process control

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Neural networks with robust backpropagation learning algorithm

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Artificial Neural Network Processing of Stripping Analysis Responses for Identifying and Quantifying Heavy Metals in the Presence of Intermetallic Compound Formation

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Multivariate nonlinear modelling of fluorescence data by neural network with hidden node pruning algorithm

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Modeling of Property Prediction from Multicomponent Analytical Data Using Different Neural Networks

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Classification and Quantitation of 1H NMR Spectra of Alditols Binary Mixtures Using Artificial Neural Networks

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Aspects of network training and validation on noisy data

Derks, E. P. P. A., & Buydens, L. M. C. (1998) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(98)00053-7 · Cited by 29 · see citing works

Use of Pyrolysis Mass Spectrometry with Supervised Learning for the Assessment of the Adulteration of Milk of Different Species

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Network training and architecture optimization by a recursive approach and a modified genetic algorithm

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Correction of non-linearities in spectroscopic multivariate calibration by using transformed original variables and PLS regression

Verdú-Andrés, J., Massart, D. L., Ménardo, C., et al. (1997) · Analytica Chimica Acta · doi:10.1016/s0003-2670(97)00271-7 · Cited by 23 · see citing works

Robust back propagation algorithm as a chemometric tool to prevent the overfitting to outliers

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Computational neural networks for the evaluation of biosensor FIA measurements

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Determination of the representativity between two multidimensional data sets by a comparison of their structure

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Evaluation of pH field effect transistor measurement signals by neural networks

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Quantitative analysis of paper coatings using artificial neural networks

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Neural network learning to non-linear principal component analysis

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Colored information from a black box?

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Quantitative determination of polymer and mineral content in paper coatings by infrared spectroscopy. Improvements by non-linear treatments

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An Application of Artificial Neural Networks. Simultaneous Determination of the Concentration of Sulfur Dioxide and Relative Humidity with a Single Coated Piezoelectric Crystal

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Modelling metabolic energy by neural networks

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Confidence intervals for calibration with neural networks

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Comment on a recent sensitivity analysis of radial base function and multi-layer feed-forward neural network models

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Aspects of network training and validation on noisy data

Derks, E. P. P. A., & Buydens, L. M. C. (1998) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(98)00054-9 · Cited by 10 · see citing works

Statistical assessment of a new criterion for selecting the number of factors in factor analysis

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Bioreactor monitoring with spectroscopy and chemometrics: a review

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Spectral pre and post processing for infrared and Raman spectroscopy of biological tissues and cells

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Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives

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PROGNOSTICATION OF BREAST CANCER BY MULTIVARIATE METHODS.

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Why Multivariate Methods are Usually Vital

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Multivariate analysis and anthropological applications

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Multivariate Analysis of Hydrological Variables

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Multivariate Methods in Research

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