flch8eg3.m

刚刚接触神经网络的朋友们看了这本书会有一定得帮助的！！

%ch8.3
clc;
clear;
close all;
%%%%%%%%%%%%%%%%%%%%%%%%%训练样本%%%%%%%%%%%%%%%%%%%%%%%%%
P=-1:0.1:1;
T=[-0.9602 -0.5770 -0.0729 0.3771 0.6405 0.6600 0.4609 ...
    0.1336 -0.2013 -0.4344 -0.5000 -0.3930 -0.1647 0.0988 ...
    0.3072 0.3960 0.3449 0.1816 -0.0312 -0.2189 -0.3201];
plot(P,T,'+');           %绘制输入/输出矢量点
xlabel('输入矢量P');
ylabel('目标矢量T');
%%%%%%%%%%%%%%%%%%%%%设计一个径向基函数网络%%%%%%%%%%%%%%%
p=-3:.1:3;
a=radbas(p);
plot(p,a)              %绘制输入输出二维图形
xlabel('输入p');
ylabel('输出a');
%%%%%%%%%%%%%%%%%%%%%%%径向基传递函数权值之和%%%%%%%%%%%%%
a2=radbas(p-1.5);
a3=radbas(p+2);
a4=a+a2*1+a3*0.5;
plot(p,a,'b-',p,a2,'b-',p,a3,'b-',p,a4,'m--')
xlabel('输入p');
ylabel('输出a');
eg=0.02;
sc=1;
net=newrb(P,T,eg,sc);               %创建一个神经网络
Newrb,neurons=0,sse=3.69051  
%%%%%%%%%%%%%%%%%%%%%%%%网络测试%%%%%%%%%%%%%%%%%%%%%%%%%%
plot(P,T,'+');
xlabel('输入');
X=-1:.01:1;
Y=sim(net,X);                      %程序仿真
hold on 
plot(X,Y);
hold off
legend({'目标','输出'});           %在图形中插入注释