字母识别.txt

字母识别源程序,能够对26个字母进行识别

%初始化
[alphabet,targets]=prprob;
[R,Q]=size(alphabet);
[S2,Q]=size(targets);
S1=10;
[R,Q]=size(alphabet);
[S2,Q]=size(targets);
P=alphabet;
net=newff(minmax(P),[S1 S2],{'logsig' 'logsig'},'traingdx');
net.LW{2,1}=net.LW{2,1}*0.01;
net.b{2}=net.b{2}*0.01;

%无噪声训练

T=targets;
net.performFcn='sse';
net.trainParam.goal=0.1;
net.trainParam.show=20;
net.trainParam.epochs=5000;
net.trainParam.mc=0.95;
[net,tr]=train(net,P,T);

%有噪声训练

netn=net;
netn.trainParam.goal=0.6;
netn.trainParam.epochs=300;
T=[targets targets targets targets];
for pass=1:10
P=[alphabet,alphabet,...
(alphabet+randn(R,Q)*0.1),...
(alphabet+randn(R,Q)*0.2)];
[netn,tr]=train(netn,P,T);
end

%再次无噪声训练p117

netn.trainParam.goal=0.1;
netn.trainParam.epochs=500;
net.trainParam.show=5;
P=alphabet;
T=targets;
[netn,tr]=train(netn,P,T);

TRAINGDX,Epoch 0/500,sse 0.0593806/0.1,Gradieng
TRAINGDX,Performance goal met.

%系统性能

noise_range=0:.05:.5
max_test=100;
network1=[];
network2=[];
T=targets;
for noiselevel=noise_range
errors1=0;
errors2=0;
for i=1:max_test
P=alphabet+randn(35,26)*noiselevel;
A=sim(net,P);
AA=compet(A);
errors1=errors1+sum(sum(abs(AA-T)))/2;
An=sim(netn,P);
AAn=compet(An);
errors2=errors2+sum(sum(abs(AAn-T)))/2;
end
network1=[network1 errors1/26/100];
network2=[network2 errors2/26/100];
end
plot(noise_range,network1*100,'--',noise_range,network2*100);
title('识别误差')；
xlable('噪声指标');
ylable('无噪声训练网络 - -  有噪声训练网络 - - -')；

%识别字母(A)

noisyJ=alphabet(:,1)+randn(35,1)*2;
plorchar(noisyJ);

A2=sim(net,noisyJ);
A2=compet(A2);
answer=find(compet(A2)==1);
plotchar(alphabet(:,answer));