Abstract
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.
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Eitzinger, C. Nonsmooth training of fuzzy neural networks. Soft Computing 8, 443–448 (2004). https://doi.org/10.1007/s00500-003-0299-6
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DOI: https://doi.org/10.1007/s00500-003-0299-6