《高等应用数学问题的MATLAB 求解》 的例题全部代码

x=0:.5:10; y=0.12*exp(-0.213*x)+0.54*exp(-0.17*x).*sin(1.23*x); x0=[0:0.1:10]; y0=0.12*exp(-0.213*x0)+0.54*exp(-0.17*x0).*sin(1.23*x0); net=newff([0,10],[5,1],{'tansig','tansig'}); net.trainParam.epochs=1000; % 设置最大步数 net=train(net,x,y); % 训练神经网络 figure; y1=sim(net,x0); plot(x,y,'o',x0,y0,x0,y1,':'); [net.IW{1} net.LW{2,1}'] % 隐层权值和输出层权值 net=newff([0,10],[5,1],{'tansig','tansig'}); net.trainParam.epochs=100; net.trainFcn='trainlm'; [net,b1]=train(net,x,y); net=newff([0,10],[5,1],{'tansig','tansig'}); net.trainParam.epochs=100; net.trainFcn='traincgf'; [net,b2]=train(net,x,y); net=newff([0,10],[5,1],{'tansig','tansig'}); net.trainParam.epochs=100; net.trainFcn='traingdx'; [net,b3]=train(net,x,y); semilogy(b1.epoch,b1.perf); hold on semilogy(b2.epoch,b2.perf,'--'); semilogy(b3.epoch,b3.perf,':') net=newff([0,10],[5,1],{'tansig','logsig'}); net.trainParam.epochs=100; net.trainFcn='trainlm'; [net,b2]=train(net,x,y); net=newff([0,10],[5,1],{'logsig','tansig'}); [net,b3]=train(net,x,y); net=newff([0,10],[5,1],{'logsig','logsig'}); [net,b4]=train(net,x,y); semilogy(b1.epoch,b1.perf); hold on; semilogy(b2.epoch,b2.perf,'--'); semilogy(b3.epoch,b3.perf,':'); semilogy(b4.epoch,b4.perf,'-.') net=newff([0,10],[15,1],{'tansig','tansig'}); net.trainParam.epochs=100; net.trainFcn='trainlm'; [net,b2]=train(net,x,y); figure; y1=sim(net,x0); plot(x0,y0,x0,y1,x,y,'o')