Nonsmooth training of fuzzy neural networks

The integration of fuzzy methods and neural networks often leads to nonsmoothness of the neural network and, consequently, to a nonsmooth training problem. It is shown, that smooth training methods as e.g. backpropagation fail to converge in this case. Thus a method – based on so called bundle-methods – for training of nonsmooth neural network is presented. Numerical results obtained from a character recognition problem show, that this method still converges where backpropagation fails.