RBf.rar_distance

clear all clc P = xlsread ('264 temperature data.xlsx'); T = xlsread ('264 binary LC data.xlsx'); %[a b]=size (P); %k=(1:b); plot(P,T,'*'); title('Training Vectors'); xlabel('Input Vector P'); ylabel('Target Vector T'); eg = 1e-35; % sum-squared error goal sc = 50; % spread constant net = newrb(P,T,eg,sc); plot(P,T,'*'); xlabel('Input'); X = xlsread ('50 temperature data.xlsx'); Y1= xlsread ('50 binary LC data.xlsx'); [a b]=size (X); k=(1:b); %y = xlsread ('Leakage current Test.xlsx'); Y = net(X); for i = 1:b if Y(i) < 0.5, Y(i) = 0; else Y(i) = 1; end end c=sum(Y==Y1) disp(['Accuracy is :',num2str(c*100/b),'%']) disp(['Error is :',num2str((b-c)*100/b),'%']) %er = Y1(k)-Y(k) %er2 = sqrt( (er(:)' * er(:)) / length(er(:)) ); hold on; figure plot(k,Y1,'-',k,Y,'*'); hold off; legend({'Target','Output'}) %save tryRBF.mat