Abstract
In this note, we introduce and study a concept of fuzzy equalization. Fuzzy equalization concerns a process of building information granules that are semantically and experimentally meaningful. The experimental relevance of a given information granule (fuzzy set) is directly linked with an encapsulation of a certain experimental evidence conveyed by the respective probability density function of available data. We establish a detailed equalization algorithm developed for triangular fuzzy sets. The study elaborates on the role of the fuzzy equalization in system design.
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