フィルターのクリア

DFT takes too long to run

1 回表示 (過去 30 日間)
Anonymous
Anonymous 2021 年 10 月 31 日
回答済み: Sulaymon Eshkabilov 2021 年 10 月 31 日
I am creating a PSD plot from a DFT after analyzing an audio file. It is taking so long to run. Is there a way to shorten the run time?
% Plotting Audio to Find Sample Rate
[y,Fs] = audioread('guitar.wav');
fprintf('Sampling Rate = %f samples/s', Fs) %sampling rate
samples=[1,length(y)-(3.5*Fs)]; %cut of the dissipated section of audio
[y1,Fs] = audioread('guitar.wav',samples);
format shortg;
dt = 1/Fs;
t = 0:dt:(length(y1)*dt)-dt; % time values
t2 = transpose(t);
figure(1)
plot(t,y1);
xlabel('Seconds');
ylabel('Amplitude');
T = max(t2); %sampling period, period (length of sampling in DFT) [s]
w = 2*pi/T; % angular frequency (based on *entire* sample time for DFT)
L = length(t2); % number of samples
% Discrete Fourier Transform (DFT)
a0 = 2/L*sum(y1); % constant term
N = floor(L/2); % maximum of floor(L/2): interesting/necessary part
a = zeros(N,1); b = a; % pre-allocate
Y = a0/2*ones(1,L); %allocate space for Y
for n = 1:N % find the first N coefficeients
a(n) = 2/L*sum( y1.*cos(w*n*t2) ); % sum over *samples*
b(n) = 2/L*sum( y1.*sin(w*n*t2) ); % sum over *samples*
Y = Y + a(n)*cos(n*w*t2) + b(n)*sin(n*w*t2); % estimated function
end
% Plot PSD
W = w*(1:N)'; % frequency range
P = sqrt(a.^2 + b.^2); % calculate power
figure(2); % Plot PSD in rad/s
plot(W,20*log10(P),'ko-'); % plot power [dB] against frequency [rad/s]
grid on; axis tight; set(gca,'fontsize', 14);
xlabel('\omega [rad/s]','fontsize', 14); ylabel('Power [dB]','fontsize', 14);
% Plot PSD in Hz
figure(3);
plot(w/(2*pi)*(1:N),20*log10(P),'ko-'); % plot power [dB] against frequency [Hz]
grid on; axis tight; set(gca,'fontsize', 14);
xlabel('f [Hz]','fontsize', 14); ylabel('Power [dB]','fontsize', 14);

採用された回答

Sulaymon Eshkabilov
Sulaymon Eshkabilov 2021 年 10 月 31 日
First of all it looks like that the heavy calc burden is occuring within [for .. end] loop. Therefore, a(n) and b(n) should be computed without a loop just using a vectorization. E.g.:
n = 1:N;
[NN, T2]=meshgrid(n,t2);
a = 2/L*sum(y1.*cos(w*NN.*T2));
b = 2/L*sum( y1.*sin(w*NN.*T2));
Y = sum(a.*cos(NN*w.*T2) + b.*sin(NN*w.*T2));

その他の回答 (0 件)

カテゴリ

Help Center および File ExchangeParametric Spectral Estimation についてさらに検索

製品


リリース

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by