%径向基网络（先聚类，后训练）
%先以K－均值聚类算法聚类，确定聚类中心，后训练网络，高斯函数的宽度参数取定值sigma=max([sum((z1-z2).^2),sum((z1-z3).^2),sum((z3-z2).^2)])/sqrt(2*3)
% 运行时间较长，查全率、查准率也比较差，原因可能是某些不同样本之间特征值差别不大，导致聚类不准确，聚类中心与实际中心不一致，（结果与聚类训练同时进行
% 的差别不大）
clear Re Pr
c=load('ccc.txt');
q1=3 ;%q1为常向量，表示神经元的个数
Ir=0.0121; max_epoch=1500;
EE=zeros(length(q1),max_epoch);
res=zeros(size(q1));%res将要存储误差向量，这里先置零
aa=1;
clear oi ok wwji wwkj b1 b2 deltak deltao yy result cout1 count2 E
tic
ceshiyangben=c;err_goal=0.05;
for i=1:59
target(i,:)=[0 0 1];
end
for i=60:131
target(i,:)=[0 1 0];
end
for i=132:178
target(i,:)=[1 0 0];
end
E=[];T=target';%mubiaoxiangliang
q=q1(aa);
[m,n]=size(ceshiyangben);[s2,s1]=size(T);
for i=2:n;
for j=1:m
ceshiyangben(j,i)=ceshiyangben(j,i)/max(ceshiyangben(:,i));
end
end %归一化
w=ceshiyangben';
z1=w(:,1);z2=w(:,2);z3=w(:,3); I=1; %1
for j=1:15
w1=[];w2=[];w3=[];
for i=1:178
if (sqrt(sum(w(:,i)-z1(:,j))^2)<sqrt(sum(w(:,i)-z2(:,j))^2))&(sqrt(sum(w(:,i)-z1(:,j))^2)<sqrt(sum(w(:,i)-z3(:,j))^2))
w1=[w1,w(:,i)];[h,n1]=size(w1);
else if (sqrt(sum(w(:,i)-z2(:,j))^2)<sqrt(sum(w(:,i)-z1(:,j))^2))&(sqrt(sum(w(:,i)-z2(:,j))^2)<sqrt(sum(w(:,i)-z3(:,j))^2))
w2=[w2,w(:,i)];[h,n2]=size(w2);
else w3=[w3,w(:,i)];[h,n3]=size(w3);
end
end
end
z1=[z1,mean(w1')'];z2=[z2,mean(w2')'];z3=[z3,mean(w3')'];
w11=w1;w22=w2;w33=w3;
[a,i]=size(z1); [a,k]=size(z2); [a,m]=size(z3);
if (z1(:,i)==z1(:,i-1))&(z2(:,k)==z2(:,k-1))&(z3(:,m)==z3(:,m-1))
break
end
end
Wki=0.2*rands(3,q); %
b2=0.1*rands(3,1);%—随机给定隐含层、输出层偏值
wwkj=[b2 Wki];
P=ceshiyangben';
count1=zeros(1,3);
count2=zeros(1,3);
z1=z1(:,j);z2=z2(:,j);z3=z3(:,j); %聚合中心
r1=sqrt(sum((P-z1*ones(1,178)).^2));r2=sqrt(sum((P-z2*ones(1,178)).^2));r3=sqrt(sum((P-z3*ones(1,178)).^2)); % ||X-W||
for kk=1:max_epoch
sigma=max([sum((z1-z2).^2),sum((z1-z3).^2),sum((z3-z2).^2)])/sqrt(2*3);
ojj1=exp(-r1.^2/(2*sigma^2)); %高斯函数
ojj2=exp(-r2.^2/(2*sigma^2));
ojj3=exp(-r3.^2/(2*sigma^2));
ojj=[ojj1;ojj2;ojj3];
oj1=[-ones(178,1) ojj'];
netk=wwkj*oj1';
oo=logsig(netk);%3-178
errr=T-oo;
sse=mse(errr);
deltao=errr.*oo.*(ones(3,178)-oo);%3-178
if(sse<err_goal)
break;
end
wwkj=wwkj+Ir*(deltao*oj1);
E=[E,sse];
end
res(aa)=norm(errr);
EE(aa,:)=E;
toc
%yangbenceshi
r1=sqrt(sum((P-z1*ones(1,178)).^2));r2=sqrt(sum((P-z2*ones(1,178)).^2));r3=sqrt(sum((P-z3*ones(1,178)).^2));
ojjj1=exp(-r1.^2/(2*sigma^2)); %11 178
ojjj2=exp(-r2.^2/(2*sigma^2));
ojjj3=exp(-r3.^2/(2*sigma^2));
ojjj=[ojj1;ojj2;ojj3];
ojj1=[-ones(178,1) ojj'];
netkk=wwkj*oj1';
ooo=logsig(netk);%3-178
for j=1:s2
for i=1:178
yy(j,i)=round(oo(j,i));
end
end
for h=1:178
if yy(:,h)==T(:,h)
if h<=59
result(1,h)=1;count1(1,1)=count1(1,1)+1;
elseif h<=131&h>59
result(1,h)=2;count1(1,2)=count1(1,2)+1;
elseif h<=178&h>131
result(1,h)=3;count1(1,3)=count1(1,3)+1;
end
else
result(1,h)=0;
end
end
Rresult(aa,:)=result;
for hh=1:178
if yy(:,hh)==[0 0 1]'
count2(1,1)=count2(1,1)+1;
elseif yy(:,hh)==[0 1 0]'
count2(1,2)=count2(1,2)+1;
elseif yy(:,hh)==[1 0 0]'
count2(1,3)=count2(1,3)+1;
end
end
Re(aa,:)=count1./[59 72 47];
Pr(aa,:)=count1./count2;
for dd=1:length(q1)
plot(EE(dd,:))
hold on
end
number=find(res==min(res));
Re3=Re
Pr3=Pr
figure
plot(Rresult(1,:)')
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