Fuzzy neural network approach for noninvasive diagnosis of digestive diseases using wavelet comparing to classification followed by fuzzy C-mean algorithm

In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the processing, the extracted signal in wavelet domain is registered. Genetic Algorithm (G.A) with binary chromosomes is used for feature selection to reduce the dimensions of feature space. Classification of digestive diseases was carried out by fuzzy neural network and fuzzy C-means algorithm. Eventually the two methods were compared. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.