带宽均值8.m

各种SVM分类算法

clear all
for k=1:40
fname=sprintf('D:\\样本\\speech\\%d.wav',k);
x=wavread(fname);
x=x(:,1);
[c,l]=wavedec(x,3,'db4');
ca=appcoef(c,l,'db4',3);%近似系数
x=ca;
enframex=enframe(x,128,64);%对信号x分帧处理，每帧有128个采样点，相邻帧之间有50%的叠加率
[row,col]=size(enframex);%返回行，列，每一行代表一帧，每一列表示1到128个采样点
 A=abs(enframex).^2;
 for j=1:row
   energy(j)=sum(A(j,:));
 end
for j=1:row
   sum1(j)=0;
   for i=1:col
   sum1(j)=sum1(j)+i*A(j,i);
   end
end
centroid=sum1./energy;
for j=1:row
    sum2(j)=0;
    for i=1:col
        sum2(j)=sum2(j)+(i-centroid(j)).^2*A(j,i);
    end
end
 bandwidth=sum2./energy;
speechbandwidthjuzhi(k,1)=mean(bandwidth);
end
speechbandwidthjuzhi


clear all
for k=1:40
fname=sprintf('D:\\样本\\music\\%d.wav',k);
x=wavread(fname);
x=x(:,1);
[c,l]=wavedec(x,3,'db4');
ca=appcoef(c,l,'db4',3);%近似系数
x=ca;
enframex=enframe(x,128,64);%对信号x分帧处理，每帧有128个采样点，相邻帧之间有50%的叠加率
[row,col]=size(enframex);%返回行，列，每一行代表一帧，每一列表示1到128个采样点
 A=abs(enframex).^2;
 for j=1:row
   energy(j)=sum(A(j,:));
 end
for j=1:row
   sum1(j)=0;
   for i=1:col
   sum1(j)=sum1(j)+i*A(j,i);
   end
end
centroid=sum1./energy;
for j=1:row
    sum2(j)=0;
    for i=1:col
        sum2(j)=sum2(j)+(i-centroid(j)).^2*A(j,i);
    end
end
 bandwidth=sum2./energy;
musicbandwidthjuzhi(k,1)=mean(bandwidth);
end
musicbandwidthjuzhi


clear all
for k=1:40
fname=sprintf('D:\\样本\\speech with music\\%d.wav',k);
x=wavread(fname);
x=x(:,1);
[c,l]=wavedec(x,3,'db4');
ca=appcoef(c,l,'db4',3);%近似系数
x=ca;
enframex=enframe(x,128,64);%对信号x分帧处理，每帧有128个采样点，相邻帧之间有50%的叠加率
[row,col]=size(enframex);%返回行，列，每一行代表一帧，每一列表示1到128个采样点
 A=abs(enframex).^2;
 for j=1:row
   energy(j)=sum(A(j,:));
 end
for j=1:row
   sum1(j)=0;
   for i=1:col
   sum1(j)=sum1(j)+i*A(j,i);
   end
end
centroid=sum1./energy;
for j=1:row
    sum2(j)=0;
    for i=1:col
        sum2(j)=sum2(j)+(i-centroid(j)).^2*A(j,i);
    end
end
 bandwidth=sum2./energy;
swmbandwidthjuzhi(k,1)=mean(bandwidth);
end
swmbandwidthjuzhi