Computational methods for the analysis of chemical sensor array data from volatile analytes.

By P. Jurs, Gregory A. Bakken, H. McClelland. Chemical Reviews, 2000

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Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries (2011, background): “There are several reviews on the subject of e-nose and e-tongue technology, including reviews on e-noses [11,12], biomimetic/biotechnology e-nose and/or e-tongue sensing systems [5,13-15], applications for e-noses and e-tongues [2,16], neural networks for e-noses [17], pattern recognition techniques”
Detection of Adulteration in Saffron Samples Using Electronic Nose (2015, methodology): “These methods are based on whether the technique is used for quantification or classification.[27] Statistical methods are parametric and include principal component analysis (PCA), linear discriminant analysis (LDA), principal component regression (PCR), partial least square (PLS), and clustering a”
High‐Temperature Ceramic Gas Sensors: A Review (2006, methodology): “The nonlinearity problem can be alleviated by using different versions of PLS, for example poly-PLS, which uses a polynomial fit for the PLS inner relation or some novel nonlinear extension of linear PLS.67,68 But these methods require high computational costs and the results of these calculations a”
Detection and identification of proteins using nanoparticle-fluorescent polymer 'chemical nose' sensors. (2007, methodology): “The raw data obtained were subjected to LDA to differentiate the fluorescence response patterns of the nanoparticle–PPE systems against the different protein target”