
about psd estimation by FFT
11 ビュー (過去 30 日間)
古いコメントを表示
Abdullah Talha Sözer
2022 年 11 月 10 日
コメント済み: Abdullah Talha Sözer
2022 年 11 月 11 日
Hi,
In topic "Power Spectral Density Estimates Using FFT (https://www.mathworks.com/help/signal/ug/power-spectral-density-estimates-using-fft.html)", why are squared dft values multipled by (1/(fs*N))?
fs = 1000;
t = 0:1/fs:1-1/fs;
x = cos(2*pi*100*t) + randn(size(t));
N = length(x);
xdft = fft(x);
xdft = xdft(1:N/2+1);
psdx = (1/(fs*N)) * abs(xdft).^2;
psdx(2:end-1) = 2*psdx(2:end-1);
freq = 0:fs/length(x):fs/2;
0 件のコメント
採用された回答
Askic V
2022 年 11 月 10 日
It is because of Parseval's theorem, which expresses the energy of a signal in time-domain in terms of the average energy in its frequency components

In this case, n and k are integers, but actually these are samples i.e. discrete time intervals, so they can be considered as n*deltaT, in such case it is
deltaT is a sample time period i.e. deltaT = 1/Fs where Fs is a sampling frequency.
That is why 1/(fs*N)!
その他の回答 (0 件)
参考
カテゴリ
Help Center および File Exchange で Parametric Spectral Estimation についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!