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Neurofuzzy systems are computing architectures whose main features arise as an effect of an important synergy occurring between two fundamental facets of information processing such as fuzzy computing and neurocomputing. Their underpinning is in a complementary character of fuzzy sets and neural networks. The latter is oriented toward more numeric processing of massive data. On the other hand, fuzzy...
This paper suggests a new type of elementary unit for neural fuzzy networks based on the concept of nullnorm. A nullnorm is a category of fuzzy set-oriented operators that generalizes triangular norms and conorms. The new unit, called nullneuron, is a generalization of and or logic-based neurons parametrized by an element u, called the absorbing element. If the absorbing element u = 0, then the nullneuron...
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