我试图找到我的频域信号的最大幅度,但是最大值似乎发生在 0 Hz 左右。我尝试了几种方法,例如减法mean of my signal
,也尝试过使用detrend
,但似乎都没有。
clear all;
clear max;
clc;
[song,FS] = wavread('c scale fast.wav');
sound(song,FS);
P = 20000;
N=length(song); % length of song
t=0:1/FS:(N-1)/FS; % define time period
song = sum(song,2);
song=abs(song);
% d = fdesign.bandpass('N,Fst1,Fp1,Fp2,Fst2',120,59,60,1000,1001,44100);
% h = design(d,'window');
% x = filter(h,song);
% Plot time domain signal
figure(1);
subplot(2,1,1)
plot(t,3*song)
title('Wave File')
ylabel('Amplitude')
xlabel('Length (in seconds)')
%ylim([-1.1 1.1])
xlim([0 N/FS])
%----------------------Finding the envelope of the signal-----------------%
% Gaussian Filter
x = linspace( -1, 1, P); % create a vector of P values between -1 and 1 inclusive
sigma = 0.335; % standard deviation used in Gaussian formula
myFilter = -x .* exp( -(x.^2)/(2*sigma.^2)); % compute first derivative, but leave constants out
myFilter = myFilter / sum( abs( myFilter ) ); % normalize
% Plot Gaussian Filter
subplot(2,1,2)
plot(myFilter)
title('Edge Detection Filter')
% fft convolution
myFilter = myFilter(:); % create a column vector
song(length(song)+length(myFilter)-1) = 0; %zero pad song
myFilter(length(song)) = 0; %zero pad myFilter
edges =ifft(fft(song).*fft(myFilter));
tedges=edges(P:N+P-1); % shift by P/2 so peaks line up w/ edges
tedges=tedges/max(abs(tedges)); % normalize
%---------------------------Onset Detection-------------------------------%
% Finding peaks
maxtab = [];
mintab = [];
x = (1:length(tedges));
min1 = Inf;
max1 = -Inf;
min_pos = NaN;
max_pos = NaN;
lookformax = 1;
for i=1:length(tedges)
peak = tedges(i:i);
if peak > max1,
max1 = peak;
max_pos = x(i);
end
if peak < min1,
min1 = peak;
min_pos = x(i);
end
if lookformax
if peak < max1-0.01
maxtab = [maxtab ; max_pos max1];
min1 = peak;
min_pos = x(i);
lookformax = 0;
end
else
if peak > min1+0.05
mintab = [mintab ; min_pos min1];
max1 = peak;
max_pos = x(i);
lookformax = 1;
end
end
end
% % Plot song filtered with edge detector
figure(2)
plot(1/FS:1/FS:N/FS,tedges)
title('Song Filtered With Edge Detector 1')
xlabel('Time (s)')
ylabel('Amplitude')
ylim([-1 1.1])
xlim([0 N/FS])
hold on;
plot(maxtab(:,1)/FS, maxtab(:,2), 'ro')
plot(mintab(:,1)/FS, mintab(:,2), 'ko')
max_col = maxtab(:,1);
peaks_det = max_col/FS;
No_of_peaks = length(peaks_det);
% song = detrend(song);
%---------------------------Performing FFT--------------------------------%
for i = 2:No_of_peaks
song_seg = song(max_col(i-1):max_col(i)-1);
L = length(song_seg);
NFFT = 2^nextpow2(L); % Next power of 2 from length of y
seg_fft = fft(song_seg,NFFT);%/L;
f = FS/2*linspace(0,1,NFFT/2+1);
seg_fft2 = 2*abs(seg_fft(1:NFFT/2+1));
L5 = length(song_seg);
figure(1+i)
plot(f,seg_fft2)
title('Frequency spectrum of signal')
xlabel('Frequency (Hz)')
%xlim([0 2500])
ylabel('|Y(f)|')
ylim([0 300])
end
如何避免这种情况并正确识别每个循环中的最大值?