Sentence examples for a fuzzy system of from inspiring English sources

In this stage, a fuzzy system of high-quality rules is already formed which contains no redundancy.

The capability of a fuzzy system for making implications between antecedents and consequents makes it appropriate for complex system analysis [18, 19].

Tuning a fuzzy system to meet a given set of requirements is usually a difficult task that involves many parameters.

These fuzzy parameters capture the different uncertainties of a fuzzy system: imprecision of inputs, vagueness of antecedent linguistic labels and smoothness requirements of outputs.

A fuzzy system consists of three parts: fuzzification, defuzzification, and a fuzzy inference engine with IF-THEN-based rules.

A new method of obtaining a fuzzy system by means of a support vector machine (SVM) with a data-dependent kernel matrix is introduced.

Especially in the construction of a fuzzy system from a set of given training examples, little attention has been paid to the analysis of the trade-off between complexity and accuracy maintaining the interpretability of the final fuzzy system.

The smoothing factor of filter, i.e., α(n) is adjusted by a fuzzy system continuously for MC of each frame.

A fuzzy system is a mapping of an input data vector into a scalar output based on FL, using the fuzzyfication, fuzzy inference, and defuzzification components.

In this article, a fuzzy system with Manhattan distances of two feature vectors as input and similarity measure as output has been added to decision-making component.

If the premise variable is the state of the system, then a fuzzy system describes a wide class of nonlinear systems.