Functional equivalence between radial basis function networks and fuzzy inference systems
Jyh‐Shing Roger Jang, Chang Sun · IEEE Transactions on Neural Networks · 1993
It is shown that, under some minor restrictions, the functional behavior of radial basis function networks (RBFNs) and that of fuzzy inference systems are actually equivalent. This functional equivalence makes it possible to apply what has been discovered (learning rule, representational power, etc.) for one of the models to the other, and vice versa. It is of interest to observe that two models stemming from different origins turn out to be functionally equivalent.