how to plot a gaussian 1D in matlab
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Gadadhar Sahoo
el 1 de Dic. de 2017
Comentada: Chad MacDonald
el 2 de Ag. de 2023
for k = 1 : K
ax = linspace(min_x,max_x,100);
y = my_gaussian(x,means,vars);
plot(ax,y);
end
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Respuesta aceptada
M
el 1 de Dic. de 2017
Editada: Adam Danz
el 14 de Jul. de 2020
You can use Matlab function to construct Gaussian function :
x = 0:0.1:10;
y = gaussmf(x,[2 5]);
plot(x,y)
4 comentarios
Chad MacDonald
el 2 de Ag. de 2023
The gaussmf function evaluates a Gaussian membership function for a fuzzy logic system, which is not the same thing as a Gaussian distribution. For more information on Gaussian probability distributions, see Normal Distribution (Statistics and Machine Learning Toolbox).
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Adam Danz
el 14 de Jul. de 2020
Editada: Adam Danz
el 14 de Jun. de 2022
Fully parameterized gaussian function (no toolboxes needed)
If you don't have the Fuzzy Logic toolbox (and therefore do not have access to gaussmf), here's a simple anonymous function to create a paramaterized gaussian curve.
gaus = @(x,mu,sig,amp,vo)amp*exp(-(((x-mu).^2)/(2*sig.^2)))+vo;
- x is an array of x-values.
- mu is the mean
- sig is the standard deviation
- amp is the (positive or negative)
- vo is the vertical offset from baseline (positive or negative)
To add noise along the y-axis of the guassian,
y = gaus(___);
yh = y + randn(size(y))*amp*.10; % noise is 10% of the amp
Demo
x = linspace(-5,25,100);
mu = 10;
sig = 5;
amp = 9;
vo = -5;
y = gaus(x,mu,sig,amp,vo);
% Plot gaussian
plot(x, y, 'b-', 'LineWidth',3)
% Add noise
yh = y + randn(size(y))*amp*.10;
hold on
plot(x, yh, 'ro','markersize', 4)
grid on
title(sprintf('Guassian with \\mu=%.1f \\sigma=%.1f amp=%.1f vo=%.1f', ...
mu, sig, amp, vo))
Comparison with gaussmf()
x = linspace(-15,10,100);
mu = -5.8;
sig = 2.5;
amp = 1;
vo = 0;
y = gaus(x,mu,sig,amp,vo);
% Plot gaussian from custom function
plot(x, y, 'b-', 'LineWidth',3, 'DisplayName','Custom function')
% Plot gaussian from custom function
y2 = gaussmf(x,[sig,mu]);
hold on
plot(x, y2, 'r--', 'LineWidth',4, 'DisplayName','gaussmf()')
grid on
title(sprintf('Guassian with \\mu=%.1f \\sigma=%.1f amp=%.1f vo=%.1f', ...
mu, sig, amp, vo))
legend()
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