rbf_ybzx_xunlian.m

采用神经网络实现分类器的训练

%径向基网络（用样本中心作为聚类中心训练网络）
%以给定的三种样本的各自平均值为中心，高斯函数的宽度参数取定值sigma=0.3
%运行时间比BP网络短，查全率、查准率比BP网络稍差。
clear Re Pr
c=load('ccc.txt');
q1=3;
Ir=0.055; 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;
sigma=0.32; 
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
   Wki=0.2*rands(3,q); %
   b2=0.1*rands(3,1);%输出层偏值 
   wwkj=[b2 Wki];
   P=ceshiyangben';
   count1=zeros(1,3);
   count2=zeros(1,3);
   z1=mean((P(:,1:59))')';z2=mean((P(:,60:130))')';z3=mean((P(:,131:178))')';   %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
     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
  sigma
  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));
sigma;
Re1=Re;
Pr1=Pr;
figure
plot(Rresult(1,:)')