File:Fourier transform, Fourier series, DTFT, DFT.gif

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摘要

描述
English: A Fourier transform and 3 variations caused by periodic sampling (at interval T) and/or periodic summation (at interval P) of the underlying time-domain function.
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來源 自己的作品
作者 Bob K
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其他版本 File:Variations_of_the_Fourier_transform.tif, Derivative works of this file:  Fourier transform, Fourier series, DTFT, DFT.svg,
GIF開發
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本GIF graphic使用LibreOffice創作。
Octave/gnuplot source
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click to expand

This graphic was created with the help of the following Octave script:

pkg load signal
graphics_toolkit gnuplot
%=======================================================
% Consider the Gaussian function e^{-B (nT)^2}, where B is proportional to bandwidth.
  T = 1;
% Choose a relatively small bandwidth, so that one cycle of the DTFT approximates a true Fourier transform.
  B = 0.1;
  N = 1024;
  t = T*(-N/2 : N/2-1);                         % 1xN
  y = exp(-B*t.^2);                             % 1xN
% The DTFT has a periodicity of 1/T=1.  Sample it at intervals of 1/8N, and compute one full cycle.
% Y = fftshift(abs(fft([y zeros(1,7*N)])));
% Or do it this way, for comparison with the sequel:
  X = [-4*N:4*N-1];                             % 1x8N
  xlimits = [min(X) max(X)];
  f = X/(8*N);
  W = exp(-j*2*pi * t' * f);                    % Nx1 × 1x8N = Nx8N
  Y = abs(y * W);                               % 1xN × Nx8N = 1x8N
% Y(1)  = SUM(n=1,2,...,N): { e^(-B × t(n)^2) × e^(-j2π ×-4096/8N × t(n)) }
% Y(2)  = SUM(n=1,2,...,N): { e^(-B × t(n)^2) × e^(-j2π ×-4095/8N × t(n)) }
% Y(8N) = SUM(n=1,2,...,N): { e^(-B × t(n)^2) × e^(-j2π × 4095/8N × t(n)) }
  Y = Y/max(Y);

% Resample the function to reduce the DTFT periodicity from 1 to 3/8.
  T = 8/3;
  t = T*(-N/2 : N/2-1);                         % 1xN
  z = exp(-B*t.^2);                             % 1xN
% Resample the DTFT.
  W = exp(-j*2*pi * t' * f);                    % Nx1 × 1x8N = Nx8N
  Z = abs(z * W);                               % 1xN × Nx8N = 1x8N
  Z = Z/max(Z);
%=======================================================
hfig = figure("position", [1 1 1200 900]);

x1 = .08;                   % left margin for annotation
x2 = .02;                   % right margin
dx = .05;                   % whitespace between plots
y1 = .08;                   % bottom margin
y2 = .08;                   % top margin
dy = .12;                   % vertical space between rows
height = (1-y1-y2-dy)/2;    % space allocated for each of 2 rows
width  = (1-x1-dx-x2)/2;    % space allocated for each of 2 columns
x_origin1 = x1;
y_origin1 = 1 -y2 -height;  % position of top row
y_origin2 = y_origin1 -dy -height;
x_origin2 = x_origin1 +dx +width;
%=======================================================
% Plot the Fourier transform, S(f)

subplot("position",[x_origin1 y_origin1 width height])
area(X, Y, "FaceColor", [0 .4 .6])
xlim(xlimits);
ylim([0 1.05]);
set(gca,"XTick", [0])
set(gca,"YTick", [])
ylabel("amplitude")
%xlabel("frequency")
%=======================================================
% Plot the DTFT

subplot("position",[x_origin1 y_origin2 width height])
area(X, Z, "FaceColor", [0 .4 .6])
xlim(xlimits);
ylim([0 1.05]);
set(gca,"XTick", [0])
set(gca,"YTick", [])
ylabel("amplitude")
xlabel("frequency")
%=======================================================
% Sample S(f) to portray Fourier series coefficients

subplot("position",[x_origin2 y_origin1 width height])
stem(X(1:128:end), Y(1:128:end), "-", "Color",[0 .4 .6]);
set(findobj("Type","line"),"Marker","none")
xlim(xlimits);
ylim([0 1.05]);
set(gca,"XTick", [0])
set(gca,"YTick", [])
ylabel("amplitude")
%xlabel("frequency")
box on
%=======================================================
% Sample the DTFT to portray a DFT

FFT_indices = [32:55]*128+1;
DFT_indices = [0:31 56:63]*128+1;
subplot("position",[x_origin2 y_origin2 width height])
stem(X(DFT_indices), Z(DFT_indices), "-", "Color",[0 .4 .6]);
hold on
stem(X(FFT_indices), Z(FFT_indices), "-", "Color","red");
set(findobj("Type","line"),"Marker","none")
xlim(xlimits);
ylim([0 1.05]);
set(gca,"XTick", [0])
set(gca,"YTick", [])
ylabel("amplitude")
xlabel("frequency")
box on

說明

添加單行說明來描述出檔案所代表的內容
A Fourier transform and 3 variations caused by periodic sampling (at interval T) and/or periodic summation (at interval P) of the underlying time-domain function.

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目前2019年8月23日 (五) 14:18於 2019年8月23日 (五) 14:18 版本的縮圖1,128 × 672(59 KB)Bob Kre-color the portion of the DFT that is computed by the FFT
2014年8月2日 (六) 13:43於 2014年8月2日 (六) 13:43 版本的縮圖1,348 × 856(71 KB)Bob KUser created page with UploadWizard

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