Often application success only comes when we select specific fuzzy techniques (t-norm, membership function, etc.) — and in different applications, different techniques are the best. How to find the best technique? Exhaustive search of all techniques is not an option: there are too many of them. We need to come up with a narrow class of promising techniques, so that trying them all is realistic. In this paper, we show that such a narrowing can be obtained from transformation groups techniques motivated by N. Wiener's conjecture — which was, in its turn, motivated by observations about human vision.
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