信号特征提取程序（matlab实现）

%----4.19编 SFFS 特征选择 成功! clear; clc; %--------特征导入 请自行修改 A=imread('lsy1.gif'); [M N]=size(A); load coourfeature_0414_lsy1 %%%共生矩阵 96.14％ feature{1}=coourfeature(:,1); feature{2}=coourfeature(:,2); feature{3}=coourfeature(:,3); load fuwavefeature_0413_lsy1 %%复小波 98.26％ for i=1:13 feature{3+i}=wavefeature(:,i); end load wavefeature_0413_feixia_lsy1%%%非下采样小波 97.58％ for i=1:7 feature{16+i}=wavefeature(:,i); end load wavefeature_0417_lsy1%%小波 97.65％ for i=1:7 feature{23+i}=wavefeature(:,i); end %%%%%%%----------归一化 [m n]=size(feature{1}); for j=1:30%一共30组特征 这里 请自行修改 mx=max(feature{j}); mi=min(feature{j}); mxx=(mx-mi); mii=ones([m n])*mi; feature{j}=(feature{j}-mii)./mxx; end %-------------------------特征选择开始啦!! d=3;%d 是最终要得到的特征数 chosen=[];%%表示已选的特征 chosen=[chosen 1 ]; %-------------------------------------------------------------------------- %--先用sfs法选入3个,否则下面的运算容易陷入死循环 for j=1:3 %选4个特征 J=zeros([1 30]); for i=2:30 %一共30组特征 这里 请自行修改 [mm nn]=size(chosen); for p=1:nn if i==chosen(p) J(i)=0; break; else J(i)=J(i)-sum(sum((feature{i}-feature{chosen(p)}).^2)); end end end mi=min(J); for i=1:30 if J(i)==0 J(i)=mi; end end ma=max(J); for i=1:30 if J(i)==ma chosen=[chosen i]; break; end end end %------------------开始 while d<13 %-----------------------------1 选l个特征------------------------------------- %一个特征一个特征的选入 J=zeros([1 30]); for i=1:30 [mm nn]=size(chosen); for p=1:nn if i==chosen(p) J(i)=0; break; else J(i)=J(i)-sum(sum((feature{i}-feature{chosen(p)}).^2)); end end end mi=min(J); for i=1:30 if J(i)==0 J(i)=mi; end end [ma1 we1]=max(J); chosen=[chosen we1]; d=d+1; %-----------------------------2 去掉r个特征------------------------------------- [ch chnum]=size(chosen); J=zeros([1 chnum]);ii=0; for i=1:chnum % 去掉chosen中第i个的效果 [mm nn]=size(chosen); for p=1:nn for q=1:nn if (chosen(q)~=chosen(i)) & (chosen(p)~=chosen(i)) J(i)=J(i)-sum(sum((feature{chosen(q)}-feature{chosen(p)}).^2)); end end end end % mi=min(J); for cc=1:chnum if J(cc)==0 J(cc)=mi; end end [ma we]=max(J); if ma>ma1 chosen(we)=[]; d=d-1; end end [mm nn]=size(chosen); tezh=[]; for i=1:nn tezh=[tezh feature{chosen(i)}]; end %%%%%%%%聚类 [IDC,U]=kmeans(tezh,2); cc(IDC==1,1)=0; cc(IDC==2,1)=0.75; g=reshape(cc,M,N); figure,imshow(g); %%%%%%%%%%%%计算正确率 ju=ones(M)*0.75; for i=1:M for j=1:M/2 ju(i,j)=0; end end ju2=g-ju; prob=prod(size(find(ju2~=0)))/(m*n) 1-prob