Description Usage Arguments Details Value References See Also
Various t-norms. Each of these is a fuzzy logic generalization of the classical conjunction operation.
1 2 3 4 5 6 7 8 9 | tnorm_minimum(x, y)
tnorm_product(x, y)
tnorm_lukasiewicz(x, y)
tnorm_drastic(x, y)
tnorm_fodor(x, y)
|
x |
numeric vector with elements in [0,1] |
y |
numeric vector of the same length as |
A function T: [0,1]\times [0,1]\to [0,1] is a t-norm if for all x,y,z\in [0,1] it holds: (a) T(x,y)=T(y,x); (b) if y≤ z, then T(x,y)≤ T(x,z); (c) T(x,T(y,z))=T(T(x,y),z); (d) T(x, 1)=x.
The minimum t-norm is given by T_M(x,y)=min(x, y).
The product t-norm is given by T_P(x,y)=xy.
The Lukasiewicz t-norm is given by T_L(x,y)=max(x+y-1,0).
The drastic t-norm is given by T_D(x,y)=0 iff x,y\in [0,1), and min(x, y) otherwise.
The Fodor t-norm is given by T_F(x,y)=0 iff x+y ≤ 1, and min(x, y) otherwise.
Numeric vector of the same length as x
and y
.
The i
th element of the resulting vector gives the result
of calculating T(x[i], y[i])
.
Klir G.J, Yuan B., Fuzzy sets and fuzzy logic. Theory and applications, Prentice Hall PTR, New Jersey, 1995.
Gagolewski M., Data Fusion: Theory, Methods, and Applications, Institute of Computer Science, Polish Academy of Sciences, 2015, 290 pp. isbn:978-83-63159-20-7
Other fuzzy_logic: fimplication_minimal
,
fnegation_yager
,
tconorm_minimum
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