Keywords: Fuzzy Theory
                                                        
                                                                                                            
                                                            Neural Network
                                                        
                                                                                                            
                                                            Wavelet Transform
                                                        
                                                                                                            
                                                            and Back Propagation Algorithm
                                                        
                                                                                                                                                                                         
                                                                        
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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