- multi frame processing

- running phi estimation


git-svn-id: http://moon:8086/svn/matlab/trunk@12 801c6759-fa7c-4059-a304-17956f83a07c
This commit is contained in:
2014-07-31 07:02:33 +00:00
parent c98009734c
commit fc703d1011
+22 -12
View File
@@ -1,36 +1,46 @@
function fdet_eval(f_true, knoise_dB)
function fdet_eval(f_true, knoise_dB, numFrames)
fs = 48000;
N = 1024;
K = numFrames;
phi_true = 1;
x_true = exp(j*(2*pi*f_true/fs*(0:N-1)'+phi_true)) + sqrt(10^(knoise_dB/10))*randn(N,1);
% Adaption rate
mu = 20.0;
% Generate signal
x_true = exp(j*(2*pi*f_true/fs*(0:K*N-1)'+phi_true)) + sqrt(10^(knoise_dB/10))*randn(K*N,1);
% Initial guess
X = fft(x_true, N);
[v maxk] = max(abs(X));
f_est = (maxk-1)*fs/N
phi_est = angle(x_true(1));
mu = 1.0;
f_est = (maxk-1)*fs/N; % * (1+angle(X(maxk)))
for k=1:500
for k=1:K
xp = x_true((k-1)*N+1:k*N);
phi_est = angle(xp(1));
x_est = exp(-j*(2*pi*f_est/fs*(0:N-1)'+phi_est));
dmod(k) = sum(x_true.*x_est);
dmod(k) = sum(xp.*x_est);
err(k) = sign(imag(dmod(k)))*(1-real(dmod(k)/abs(dmod(k))))^.5;
f_est = f_est + mu*err(k);
f(k) = f_est;
phi(k) = phi_est;
end;
f_true = f_true
f_est = f_est
mean_fest = mean(f(K/2+1:K))
error_ppm = 1E6*(1-mean_fest/f_true)
close all;
subplot(3,1,1)
plot(1:lge(f), 1-real(dmod)./abs(dmod), 1:lge(f), imag(dmod)./abs(dmod)); grid;
subplot(4,1,1)
plot(1:lge(f), 1-real(dmod)./abs(dmod), 1:lge(f), imag(dmod)./abs(dmod), 1:lge(f), real(dmod)./abs(dmod)); grid;
subplot(3,1,2)
subplot(4,1,2)
plot(1:lge(f), err, '-*'); grid;
subplot(3,1,3)
subplot(4,1,3)
plot(1:lge(f), f); grid;
subplot(4,1,4)
plot(1:lge(f), angle(dmod)); grid;