학술논문
Potato creams recognition from electronic nose and tongue signals: feature extraction/selection and RBF neural networks classifiers
Document Type
Conference
Author
Source
Proceedings of the 5th Seminar on Neural Network Applications in Electrical Engineering. NEUREL 2000 (IEEE Cat. No.00EX287) Neural network applications in electrical engineering Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on. :69-74 2000
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Language
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.