A new neural network approach classifies olfactory signals with high accuracy

Artificial neural networks (ANN) become more significant in signal processing. Because ANN still have some drawbacks we developed a new neural network tool named ACMD considering several methods of resolution, existing ones as well as new ones. In order to demonstrate the capabilities of ACMD in the field of food quality, we classified signals from an electronic nose smelling different types of edible oil and honey. The accuracies achieved by ACMD were evidently greater than the accuracies obtained by ANN trained by other well-known methods. As a conclusion it seems to be worthwhile considering sophisticated ANN strategies like those integrated in ACMD.