What Is Fuzzy Logic?

2 Tutorial
In the toolbox, the AND implication methods perform an element by element
matrix operation, similar to the MATLAB function min(x,y).
a=[1 2; 3 4];
b=[2 2; 2 2];
min(a,b)
ans =
1 2
2 2
The OR implication methods perform an element by element matrix operation,
similar to the MATLAB function max(x,y).
Guidelines for Creating Custom Implication Functions
The custom implication functions must operate in the same way as
the MATLAB functions max, min, orprod and must be of the form y =
custom_imp(w,outputmf).
Here w is an nr-by-ns matrix and contains the weight of each rule. nr is the
number of rules, and ns is the number of parameters used to define the
output membership functions. w(:,j) = w(:,1) for all j, andw(i,1) is the firing
strength of the i th rule.
outputmf is an nr-by-ns matrix and contains the data for each output
membership function, where the i th row is the data for the i th output
membership function.
The following is an example of a custom implication function:
function impfun = custom_imp(w,outputmf)
impfun = min(w,outputmf);
Guidelines for Creating Custom Aggregation Functions
The custom aggregation functions must operate in the same way as
the MATLAB functions max, min, orprod and must be of the form y =
custom_agg(x).
x is an nv-by-nr matrix, which is the list of truncated output functions
returned by the implication method for each rule. nv is the number of output
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