gusucode.com > 《MATLAB神经网络超级学习手册》随书光盘源码程序 > code/6/N6_11.m
clear all clc %%%%%%%%%定义输入向量和目标向量%%%%%%%%%%%%% time=0.1:0.1:20; %时间变量 y=(rand(1,200)-0.6)*5; %定义随机输入信号 P=con2seq(y); delays=[1 2]; %神经元输入延迟量 T=P; %神经元的目标向量 %%%%%%%%%创建线性神经网络%%%%%%%%%%%%%%%%%%% net=newlin(minmax(y),1,delays,0.0005); %%%%%%%%%线性神经网络的自适应训练%%%%%%%%%%%% net.adaptParam.passes=70; [net,a,output]=adapt(net,P,T) %%%%%%%%%绘制波形%%%%%%%%%%%%%%%%%%%%%%%%%%% hold on subplot(3,1,1) plot(time,y) %随机输入信号波形 xlabel('T','position',[20,-2]); ylabel('随机输入信号s(t)') axis([0 20 -3 3]) subplot(3,1,2); output=seq2con(output); plot(time,output{1}); %预测输出信号波形 xlabel('T','position',[20,-2]); ylabel('预测输出信号y(t)') axis([0 20 -3 3]) subplot(3,1,3); e=output{1}-y; plot(time,e); %误差曲线 xlabel('time','position',[20,-2]); ylabel('误差曲线e(t)') axis([0 20 -0.2 0.2]) hold off