Feature extraction of artificial tongue data using gram-schmidt orthonormalization

In this paper we present a combined feature extraction approach for an electronic tongue. The use of wavelet decomposition technique for feature extraction, followed by orthonormalization, decreases the number of classifier inputs to the multiplication of number of classes and number of sensors. This approach leads to a higher computational efficiency. Two experiments are presented to demonstrate the procedure.