Abstract
We describe the development of a potato cream recognition system based on radial basis function neural networks from electronic nose and electronic tongue signals. Exhaustive and systematic feature extraction and selection, which are needed because of high dimensionality of signals, are performed on both instruments using various feature selection algorithms. At the end, we design the classifier based on the RBF network, and compare the results obtained from different features.
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