Fuzzy Logic S-Norm (OR)
y=snorm( x , class [,class_par] )
matrix of real with size [m,n].
matrix of real with size [m,1].
string, s-norm class. The values can be: "dubois" for Dubois-Prade S-Norm, "yager" for Yager S-Norm, "dsum" for drastic sum S-Norm, "esum" for Einstein sum S-Norm, "asum" for algebraic sum S-Norm, "max" for maximum S-Norm.
scalar, S-Norm class parameter. "dubois" and "yager" class need this parameter.
snom
compute S-Norm class
of x
with parameter class_par
. The calculation was made taking the
j row of x
as input and put the resulting value in the j row
of y
(row oriented calculation).
"dubois"
class need 0<=class_par<=1
.
"yager"
class need class_par>0
.
x=rand(5,2); y1=snorm(x,"dubois",0.5); y2=snorm(x,"yager",2); y3=snorm(x,"dsum"); y4=snorm(x,"asum"); y5=snorm(x,"max"); | ![]() | ![]() |