File:Processing losses for 3 window functions.gif
預覽大小：565 × 599 像素。 其他解析度：226 × 240 像素 | 574 × 609 像素。
原始檔案 （574 × 609 像素，檔案大小：21 KB，MIME 類型：image/gif、0.1秒）
摘要
| 描述 |
English: Comparison of three window functions in terms of their effects on equal-strength sinusoids with additive noise. The noise "floor" is smoothed by averaging many DFTs to reveal the substantial difference in levels, caused by the different window functions. In each case, the sinusoid on the left suffers no scalloping and the one on the right exhibits worst-case scalloping. The rectangular window produces the most scalloping but lowest noise-floor. The Hann window has a higher noise floor but much less potential scalloping, which results in the lowest "worst case processing loss" of these 3 functions. |
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| 日期 | ||||
| 來源 | 自己的作品 | |||
| 作者 | Bob K | |||
| 授權許可 (重用此檔案) |
我，本作品的著作權持有者，決定用以下授權條款發佈本作品：
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| 其他版本 |
此檔案衍生的作品： Processing losses for 3 window functions.svg,
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| GIF開發 |  本GIF 點陣圖使用LibreOffice創作。 |
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| Octave/gnuplot source | click to expand
This graphic was created with the help of the following Octave script: pkg load signal
graphics_toolkit gnuplot
clear all; close all; clc
hfig= figure("position",[100 0 574 609]);
N = 256; % sams_per_fft;
window1 = rectwin(N)'/sum(rectwin(N));
window2 = hann(N)'/sum(hann(N));
window3 = blackmanharris(N)'/sum(blackmanharris(N));
%
Fs = N; % sams_per_sec;
HzPerBin = Fs/N;
F1 = -20.0*HzPerBin; % bin -20
F2 = +20.5*HzPerBin; % bin 20.5
%
L = 100000;
n = 1:L;
x = exp(j*2*pi*F1/Fs*n) + exp(j*2*pi*F2/Fs*n);
x = x + (randn(1,L) +j*randn(1,L))*1.4;
%
sams_per_offset = 0.75*N; % overlap = 25%
%
% number of samples available beyond just one FFT
excess_sams = length(x) - N;
%
j1 = floor( excess_sams / sams_per_offset );
sams_per_offset = floor( excess_sams / j1 );
num_ffts = 1 + j1;
%
% define the first block of data
samples = 1:N;
%
amplitude1 = zeros(1,N);
amplitude2 = zeros(1,N);
amplitude3 = zeros(1,N);
%
% Loop over all the available blocks
for j1 = 1 : num_ffts
amplitude1 = amplitude1 + abs(fft( x(samples) .* window1 ));
amplitude2 = amplitude2 + abs(fft( x(samples) .* window2 ));
amplitude3 = amplitude3 + abs(fft( x(samples) .* window3 ));
samples = samples + sams_per_offset;
end
%
amplitude1 = 20*log10(fftshift(amplitude1/num_ffts));
amplitude2 = 20*log10(fftshift(amplitude2/num_ffts));
amplitude3 = 20*log10(fftshift(amplitude3/num_ffts));
%
abscissa = -40:40;
set(gca,'FontSize',8)
subplot(3,1,1);
h = area(abscissa, amplitude1(abscissa +N/2+1), ...
'FaceColor', [.871 .49 0], 'edgecolor', [.871 .49 0]);
set(h,'BaseValue',-20)
set(gca, 'XTick', [-20 0 20.5], 'XTickLabel',[' '; ' '; ' '], 'YGrid','on', 'color', 'white')
title('Processing losses for sinusoids in additive noise','fontsize', 12);
xlim([-40 40])
ylim([-20 2])
ylabel('decibels')
text(-40, 3.5, 'Rectangular window')
%
subplot(3,1,2);
h = area(abscissa, amplitude2(abscissa +N/2+1), ...
'FaceColor', [.871 .49 0], 'edgecolor', [.871 .49 0]);
set(h,'BaseValue',-20)
set(gca, 'XTick', [-20 0 20.5], 'XTickLabel',[' '; ' '; ' '], 'YGrid','on', 'color', 'white')
xlim([-40 40])
ylim([-20 2])
ylabel('decibels')
text(-40, 3.5, 'Hann window')
%
subplot(3,1,3);
h = area(abscissa, amplitude3(abscissa +N/2+1), ...
'FaceColor', [.871 .49 0], 'edgecolor', [.871 .49 0]);
set(h,'BaseValue',-20)
set(gca, 'XTick', [-20 0 20.5], 'XTickLabel',[' '; ' '; ' '], 'YGrid','on', 'color', 'white')
xlim([-40 40])
ylim([-20 2])
ylabel('decibels')
text(-40, 3.5, 'Blackman-Harris')
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| 日期/時間 | 縮圖 | 尺寸 | 使用者 | 備註 | |
|---|---|---|---|---|---|
| 目前 | 2013年3月3日 (日) 14:37 | | 574 × 609（21 KB） | Bob K | Shorten three horizontal lines to make the scalloped peaks more apparent. |
| 2013年2月25日 (一) 15:29 |  | 579 × 609（21 KB） | Bob K | User created page with UploadWizard |
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