# Re: hack fuzzy identity?

Oscar Duarte (visit2@decsai.ugr.es)
Mon, 21 Sep 1998 22:29:06 +0200 (MET DST)

Karl:

You can get the identity function very easy if you use a "heigth"
defuzzifying method:

Define 3 fuzzy sets in the input and output spaces as trapezoids (I have
supposed Universe of discurse =[0,1] )
Input:
c1:(0,0,0,0.5)
c2:(0,0.5,0.5,1)
c3:(0.5,1,1,1)
Outnput:
d1:(0,0,0,0.5)
d2:(0,0.5,0.5,1)
d3:(0.5,1,1,1)

Define 3 rules:
if c1 then d1
if c2 then d2
if c3 then d3

You will get the identity function...

Oscar Duarte
http://ohm.ingsala.unal.edu.co/ogduarte

At 02:37 AM 9/11/98 +0200, karl wrote:
>
>I was wondering what fuzzy membership sets would give
>me the identity function, making an inference rule act like y = x.
>
>I have an input x, and an output y, that both range between 0 and 1.
>I want the defuzzified value of y to equal the crisp value of x. I would
>like to write a rule like this
>
>if (identity_x)
>
> identity_y
>}
>
>where the identity are fuzzy sets. The only things that has worked
>so far is an enormous number of little triangles, at each interval of
>x and y
>
>if (one_x)
>
> one_y
>} else if (two_x)
>
> two_y
>} else if (three_x)
>
> three_y
>}
>... and so on
>
>
>gah!!! what a hack.
>
>Any ideas?
>
> Karl
>
>
>
>
>
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