A novel recognition method for electronic nose using artificial neural network and fuzzy recognition

Recently, ANNs (artificial neural networks) have been widely used in odour recognition using an artificial olfactory system, an electronic nose. However, when classes have a great difference in shape, volume and density or they are overlapped with each other, the current ANN methods sometimes fail to get a good classification. To solve these problems, an improved odour-recognition method that combines the FCMA (fuzzy c-means algorithm) with an RBF (radial basic function neural network) is described in this paper. Application of this method to the odour-pattern classification of some gas mixtures using an electronic nose based on a gas sensing sensor array has been carried out. Both the computer simulations and the odour-recognition experimental results demonstrate the unusual effectiveness and the good recognition performance of the above-mentioned method.