www.gusucode.com > MATLAB神经网络实例与精析随书源程序 > 第11章 用GUI设计神经网络/fit_test.m

    %fit_test.m
% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by NFTOOL
% Created Sun Mar 11 15:31:43 CST 2012
%
% This script assumes these variables are defined:
%
%   x - input data.
%   y - target data.

% 自定义语句------------------------------
x=0:.2:2*pi+.2;
rng(2);y=sin(x)+rand(1,length(x))*0.5;
plot(x,y,'o-');

%-----------------------------------------

inputs = x;
targets = y;

% Create a Fitting Network
hiddenLayerSize = 10;
net = fitnet(hiddenLayerSize);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,inputs,targets);

% Test the Network
outputs = net(inputs);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs)

% View the Network
view(net)
% 自定义语句-----------------------------
xx=0:.1:2*pi+.2;
yy=sin(xx)+0.25;
yx=net(xx);

plot(x,y,'o');
hold on;
plot(xx,yy,'g-');
plot(xx,yx,'r+');
legend('训练样本','正弦曲线出','实际输出');
%----------------------------------------
% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, plotfit(net,inputs,targets)
%figure, plotregression(targets,outputs)
%figure, ploterrhist(errors)