example.m

The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB lan

N=100;    
inputs=[2*rand(N,1)-1 2*rand(N,1)-1];
output=4*sin(pi*inputs(:,1))+2*cos(pi*inputs(:,2))+0.05*randn(N,1);
data=[inputs output];
save data_example data

fuzzy_g %Model selection

fuzzy_g %Training model

N_ts=50;
inputs_ts=[2*rand(N_ts,1)-1 2*rand(N_ts,1)-1];
output_ts=4*sin(pi*inputs_ts(:,1))+2*cos(pi*inputs_ts(:,2));

in=inputs_ts;
save test_example in

fuzzy_g % prediction