低帧能量比（系数）.m

各种SVM分类算法

clear all
 for i=1:20
   fname=sprintf('D:\\样本\\speech with music\\%d.wav',i);
   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=log10(abs(enframex).^2);
   energy=zeros(row,1);
   for j=1:row
     energy(j)=sum(A(j,:));
   end
    s=0;
    for j=1:row
     s=s+energy(j);
   end
   s=0.7*(s/row);
   swm(i)=0;
   for k=1:row
       if energy(k,1)<s
          swm(i)=swm(i)+1;
       end
   end
   swmshangbi(i,1)=swm(i)/row;
  end
swmshangbi
  

 

clear
for i=1:20
   fname=sprintf('D:\\样本\\speech\\%d.wav',i);
   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=log10(abs(enframex).^2);
   energy=zeros(row,1);
   for j=1:row
     energy(j)=sum(A(j,:));
   end
    s=0;
    for j=1:row
     s=s+energy(j);
   end
   s=0.7*(s/row);
   speech(i)=0;
   for k=1:row
       if energy(k,1)<s
          speech(i)=speech(i)+1;
       end
   end
   speechshangbi(i,1)=speech(i)/row;
  end
 speechshangbi
 
   

clear
for i=1:20
   fname=sprintf('D:\\样本\\music\\%d.wav',i);
   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=log10(abs(enframex).^2);
   energy=zeros(row,1);
   for j=1:row
     energy(j)=sum(A(j,:));
   end
   s=0;
    for j=1:row
     s=s+energy(j);
   end
   s=0.7*(s/row);
   music(i)=0;
   for k=1:row
       if energy(k,1)<s
          music(i)=music(i)+1;
       end
   end
  musicshangbi(i,1)=music(i)/row;
  end
 musicshangbi