This paper explores fuzzy neural trees and an approach for converting these trees into feed-forward neural network architectures. The proposed approach is unique in that it introduces the ways to use either technology as a "tool" within the framework of a model based on the other. It is of the highest significance as it results in new neural network algorithms where no time-consuming iterative training is required.
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