The conventional digital hardware computational blocks with different structures are
designed to compute the precise results of the assigned calculations. The main contribution …

The defuzzification is a critical block when implementing a fuzzy inference engine due to
different variations and also high computational power demands of defuzzification …

Interval type-2 defuzzification maps an interval type-2 fuzzy set to a crisp number. We show
that the semantic meaning of the interval type-2 fuzzy set (the associated opportunity or risk) …

Defuzzification converts a fuzzy set to a crisp value or set. Standard defuzzification methods
are the center of gravity (COG) and the mean of maxima (MOM). A popular parametric …

In this paper, a new active rule detection algorithm is proposed which is efficiently
implemented in dedicated fuzzy processors. Here, its advantages are analytically attested. A …

An efficient fuzzification algorithm named as Dynamic Precision Fuzzification (DPF) is
introduced in this paper which is mainly developed for hardware implementation. The DPF …

Fuzzy hardware is the best choice to reach high speed inference rates in knowledge based
systems. In fuzzy systems, the defuzzifier stage is the most hardware resource consumer …

Researchers traditionally solve the computational problems through rigorous and
deterministic algorithms called as Hard Computing. These precise algorithms have widely …

The number of intelligent systems which use soft-computing methods in real-world
applications is growing. General purpose processors (GPPs) are one selection of designers …