jtrbfgjnet.m

对静态对象采用rbf神经网络进行建模的源程序,经过调试,直接就可以由MATLAB运行!

function main()
samnum=100;
testsamnum=101;
sp=0.6;
errorlimit=0.1;

rand('state',sum(100*clock))
noisevar=0.01;
noise=noisevar*randn(1,samnum);
samin=8*rand(1,samnum)-4;
samoutnonoise=1.1*(1-samin+2*samin.^2).*exp(-samin.^2/2);
samout=samoutnonoise+noise;

testsamin=-4:0.08:4;
testsamout=1.1*(1-testsamin+2*testsamin.^2).*exp(-testsamin.^2/2);

figure
hold on
grid
plot(samin,samout,'k+')
plot(testsamin,testsamout,'b-')
xlabel('input x');
ylabel('output y');

[indim,maxunitnum]=size(samin);

distance=dist(samin',samin);
hiddenunitout=radbas(distance/sp);

posselected=[];
vectorsselected=[];
hiddenunitoutselected=[];
errorhistory=[];

vectorsselectfrom=hiddenunitout;

dd=sum((samout.*samout)')';
for k=1:maxunitnum
    pp=sum(vectorsselectfrom.*vectorsselectfrom)';
    denominator=dd*pp';
    [xxx,selectednum]=size(posselected);
    if selectednum>0,
        [lin,xxx]=size(denominator);
        denominator(:,posselected)=ones(lin,1);
    end
    angle=((samout*vectorsselectfrom).^2)./denominator;
    
    [value,pos]=max(angle);
    posselected=[posselected pos];
    
    hiddenunitoutselected=[hiddenunitoutselected;hiddenunitout(pos,:)];
    hiddenunitoutex=[hiddenunitoutselected;ones(1,samnum)];
    w2ex=samout*pinv(hiddenunitoutex);
    w2=w2ex(:,1:k);
    b2=w2ex(:,k+1);
    nnout=w2*hiddenunitoutselected+b2;
    SSE=sumsqr(samout-nnout)
    
    errorhistory=[errorhistory SSE];
    
    if SSE<errorlimit,break,end
    
   newvector=vectorsselectfrom(:,pos);
   projectionlen=newvector'*vectorsselectfrom/(newvector'*newvector);
   vectorsselectfrom=vectorsselectfrom-newvector*projectionlen;
end

unitcenters=samin(posselected);

testdistance=dist(unitcenters',testsamin);
testhiddenunitout=radbas(testdistance/sp);
testnnout=w2*testhiddenunitout+b2;
plot(testsamin,testnnout,'r-')

k
unitcenters
w2
b2

figure
hold on
grid
[xx,num]=size(errorhistory);
plot(1:num,errorhistory,'r-');