example2.asv

一本关于dsp的原著教材

% example 2_1 calculate propbility of each vow
clear all;
plotvow; % also load vowels.mat
%load vowels.mat;
whos;
Na=size(a,1);
Ne=size(e,1);
Ni=size(i,1);
No=size(o,1);
Ny=size(y,1);
N=Na+Ne+Ni+No+Ny;
Pa=Na/N
Pe=Ne/N
Pi=Ni/N
Po=No/N
Py=Ny/N

% exmple 2_2 plot and calculate mu and sigma for each of vows

mu_a=mean(a)
sigma_a=cov(a)
plotgaus(mu_a,sigma_a,[1,0,1]);

mu_e=mean(e)
sigma_e=cov(e)
plotgaus(mu_e,sigma_e,[0,0,1]);

mu_i=mean(i)
sigma_i=cov(i)
plotgaus(mu_i,sigma_i,[1,0,0]);

mu_o=mean(o)
sigma_o=cov(o)
plotgaus(mu_o,sigma_o,[0,1,1]);

mu_y=mean(y)
sigma_y=cov(y)
plotgaus(mu_y,sigma_y,[1,1,0]);

%example 2_3 Beysian estimator
%f1=400;f2=1800;
%f1=400;f2=1000;
%f1=530;f2=1000;
%f1=600;f2=1300;
%f1=670;f2=1300;
f1=420;f2=2500;
a_log=gloglike([f1, f2], mu_a,sigma_a)+log(Pa)
e_log=gloglike([f1, f2], mu_e,sigma_e)+log(Pe)
i_log=gloglike([f1, f2], mu_i,sigma_i)+log(Pi)
o_log=gloglike([f1, f2], mu_o,sigma_o)+log(Po)
y_log=gloglike([f1, f2], mu_y,sigma_y)+log(Py)