A new class of fuzzy neural networks with application in system modeling

Huimin Ma, A.A. El-Keib, Xingliang Ma · 2002

This paper presents a new class of fuzzy neural networks and its application to system modeling. The optimal set of fuzzy associative memory rules and weights can be identified for a given set of sample data. Test results of modeling a nonlinear system show that the proposed fuzzy neural network can accurately model a complicated nonlinear system and the model is quite robust in the sense that its modeling accuracy is much insensitive to sample data.>

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