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Summary

Description

Circular convolution can be expedited by the FFT algorithm, so it is often used with an FIR filter to efficiently compute linear convolutions. These graphs illustrate how that is possible.

Date

16 April 2008

Source

Own work

Author

Bob K

Permission
(Reusing this file)

I, the copyright holder of this work, release this work into the public domain. This applies worldwide.
In some countries this may not be legally possible; if so:
I grant anyone the right to use this work for any purpose, without any conditions, unless such conditions are required by law.

Category:Self-published work#Circular%20convolution%20example.png Category:PD-self#Circular%20convolution%20example.png

Other versions

Derivative works of this file: Circular convolution example.svg

Category:Files with derivative versions

File:Circular convolution example.svg is a vector version of this file. It should be used in place of this PNG file when not inferior.Category:Vector version available

File:Circular convolution example.png → File:Circular convolution example.svg

For more information, see Help:SVG.

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PNG development

This PNG graphic was created with LibreOffice.

Category:PNG created with LibreOffice#Circular%20convolution%20example.png

Octave/gnuplot source

click to expand

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

graphics_toolkit gnuplot

% "color" is temporary, because of gnuplot bug (see below)
hfig = figure("color", .85*[1 1 1], "position", [100 100 488 512]);
set(gca, "color", .85*[1 1 1])

xmax = 3000;

% subplot() undoes the "color" attempts above.  (gnuplot bug)
subplot(6,1,1)
L = 100;
f = ones(1,L)/L;
plot(-100:200-1, [zeros(1,100) f*L zeros(1,100)], "linewidth", 2, "color", "magenta")
set(gca, "color", "white")
title("Circular convolution example", "FontSize",12)
text(100, 1.6, "h[n]")
text(xmax/2, 0.4, '\leftarrow n \rightarrow')
ylim([0 2])
xlim([-100 xmax])
set(gca,"XTick",[]); set(gca,"YTick",[])

subplot(6,1,2)
a = [zeros(1,20) ones(1,L) zeros(1,300) 0.5*ones(1,100) zeros(1,1000-L-20-400)];
b = [zeros(1,1000-L-20) ones(1,L) zeros(1,20)];
a1 = [zeros(1,1000) a zeros(1,1000)];
b1 = [zeros(1,1000) b zeros(1,1000)];
plot(1:length(a1), a1, "color", "blue", 1:length(a1), b1, "color", "red")
set(gca, "color", "white")
text(200, 1.6, "X[n]")
ylim([0 2])
xlim([0 xmax])
set(gca,"XTick",[]); set(gca,"YTick",[])

subplot(6,1,3)
a1 = conv(a1,f);
b1 = conv(b1,f);
plot(1:length(a1), a1+b1, "color", "green", "linewidth", 2)
set(gca, "color", "white")
text(200, 1.6, "X[n] * h[n]")
ylim([0 2*max(a1)])
xlim([0 xmax])
set(gca,"XTick",[]); set(gca,"YTick",[])

subplot(6,1,4)
a = [a a a];
b = [b b b];
L = 1:length(a);
plot(L, a, "color","blue", L, b, "color","red")
set(gca, "color", "white")
text(200, 2.0, 'X_N[n]')
ylim([0 2.5])
xlim([0 xmax])
set(gca,"XTick", [1000 2000])
set(gca,"XTickLabel",["N"; "2N"])
set(gca,"YTick",[])

subplot(6,1,5)
a1 = conv(a,f);
b1 = conv(b,f);
b1(1:90) = b1(3000+[1:90]);
L = 1:length(a1);
plot(L,a1,"color","blue", L,b1, "color","red")
set(gca, "color", "white")
text(200, 1.6, 'components of X_N[n] * h[n]')
ylim([0 2*max(a1)])
xlim([0 xmax])
set(gca,"XTick",[]); set(gca,"YTick",[])

subplot(6,1,6)
c = a1+b1;
L = length(c);
k=1100;
plot(1:k, c(1:k), "color","red", k+(1:900), c(k+(1:900)), "color", "green", "linewidth", 2, (k+900+1):xmax, c((k+900+1):xmax), "color","red")
set(gca, "color", "white")
text(200, 1.6, 'X_N[n] * h[n]')
ylim([0 2*max(a1+b1)])
xlim([0 xmax])
set(gca,"XTick",[]); set(gca,"YTick",[])

text(1163, -1, "X[n] * h[n]", "fontsize", 16)
annotation("line", [.414 .414], [.136 .045])
annotation("line", [.647 .647], [.136 .045])

% I prefer the version created by the export function on the GNUPlot figure,
% because the dimensions are better.
print(hfig,"-dpng","-color", 'C:\Users\BobK\Circular convolution example.png')

Category:Convolution Category:Created with GNU Octave Category:Images with Octave source code Category:Images with Gnuplot source code