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Fuzzy Logic Tutorial Part II:

LINGUISTIC VARIABLES

By  Vadiraj Joshi

 

 

 

These are the important terms in fuzzy logic because it involves its main features. A linguistic variable allows us to describe its value qualitatively and quantitatively:  

 

 

 

-  Qualitatively: 

  • With a linguistic term.
  • Serving as the name of a fuzzy set, regarding the example we saw above it was TALL

-  Quantitatively:

  • With a number
  • Very useful to process numeric input data
  • Regarding Fuzzy Logic it was the  membership function (which expresses the meaning of the fuzzy set, its belonging

Fuzzy logic combines these two aspects of variables into a uniform framework. This is very useful because the qualitatively description is very understandable for us, and the quantitatively description is very useful to compute data and get output values.  

A fuzzy set has this dual representation, a linguistic term and a numeric value through its membership function, which maps elements in a universe of discourse (i.e. all the different heights) to their membership degree in the set. Above mentioned all are summarized into following figure 3.  


Figure 3: Fuzzy Set and Membership Function

Section 3 is about fuzzy sets in detail.

 

(You can contact author through email: vadiraj@electrosofts.com )

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