Fuzzy neural network with fuzzy signals and weights

The direct fuzzification of a standard layered feedforward neural network where the signals and weights are fuzzy sets is discussed. A fuzzified delta rule is presented for learning. Three applications are given, including modeling a fuzzy expert system; performing fuzzy hierarchical analysis based on data from a group of experts; and modeling a fuzzy system. Further applications depend on proving that this fuzzy neural network can approximate a continuous fuzzy function to any degree of accuracy on a compact set.<<ETX>>

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