📄 examp10_12.m
字号:
[x,y]=meshgrid(-3:.6:3, -2:.4:2); x=x(:)'; y=y(:)';
z=(x.^2-2*x).*exp(-x.^2-y.^2-x.*y); % 注意这三个变量均应为行向量
net=newff([-3 3; -2 2],[10,10,1],{'tansig','tansig','tansig'});
net.trainParam.epochs=1000; net.trainFcn='trainlm';
[net,b]=train(net,[x; y],z); % 训练神经网络
[x2,y2]=meshgrid(-3:.1:3, -2:.1:2); x1=x2(:)'; y1=y2(:)';
figure; z1=sim(net,[x1; y1]); z2=reshape(z1,size(x2)); surf(x2,y2,z2)
net=newff([-3 3; -2 2],[10,20,1],{'tansig','tansig','tansig'});
[net,b]=train(net,[x; y],z); % 训练神经网络
z1=sim(net,[x1; y1]); z2=reshape(z1,size(x2)); surf(x2,y2,z2)
[x,y]=meshgrid(-3:.2:3, -2:.2:2); x=x(:)'; y=y(:)';
z=(x.^2-2*x).*exp(-x.^2-y.^2-x.*y);
net=newff([-3 3; -2 2],[10,10,1],{'tansig','tansig','tansig'});
net.trainParam.epochs=100; net.trainFcn='trainlm';
net=train(net,[x; y],z);
[x1,y1]=meshgrid(-3:.1:3, -2:.1:2); a=x1; x1=x2(:)'; y1=y2(:)';
z1=sim(net,[x1; y1]); z2=reshape(z1,size(a)); surf(x2,y2,z2)
net=newff([-3 3; -2 2],[10,20,1],{'tansig','tansig','tansig'});
net=train(net,[x; y],z); % 修改节点个数后的泛化效果
figure; z1=sim(net,[x1; y1]); z2=reshape(z1,size(a)); surf(x2,y2,z2)
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -