sin_test1.m

人工神经网络资料

clear all
pi=3.14;
P = 0:0.2:pi*2;
T=sin(P);
net=newff(minmax(P),[3,1],{'tansig','purelin'},'traingda');
net.trainParam.show = 50;
net.trainParam.lr = 0.05;
net.trainParam.lr_inc = 1.05;
net.trainParam.epochs = 300;
net.trainParam.goal = 1e-2;

% net = newff(minmax(P),[10 1],{'logsig' 'logsig'},'traingdx','learngd');
%  Training Without Noise
% net.performFcn = 'mse';
% net.trainParam.goal = 0.01;
% net.trainParam.lr=0.001;
% net.trainParam.show = 100;
% net.trainParam.min_grad=1.0e-002;
% net.trainParam.epochs = 500;
% net.trainParam.mc = 0.90;
[net,tr] = train(net,P,T);
p1=0:0.3:pi*2;
Y = sim(net,P);
figure(1)
plot(P,T,'*',P,Y,'o');