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Simple real Fourier series approximation

version 1.1 (3.37 KB) by Matt Tearle
Computes coefficients for the real Fourier series approximation to a data set.

5.8K Downloads

Updated 03 Mar 2020

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Includes two functions: Fseries.m and Fseriesval.m
[a,b] = Fseries(X,Y,n) fits an nth-order Fourier expansion of the form
y = a_0/2 + Sum_k[ a_k cos(kx) + b_k sin(kx) ]
to the data in the vectors X & Y, using a least-squares fit.

Y = Fseriesval(a,b,X) evaluates the Fourier series defined by the coefficients a and b at the values in the vector X.

Extra arguments allow for rescaling of X data and sin-only or cosine-only expansions.

Example:
% Generate data
x = linspace(0,2,41)';
y = mod(2*x,1);
% Use FSERIES to fit
[a,b,yfit] = Fseries(x,y,10);
% Evaluate on finer grid
xfine = linspace(0,2)';
yfine = Fseriesval(a,b,xfine);
% Visualize results
plot(x,y,'x',x,yfit,'o',xfine,yfine)

This generates the attached image of a 10-term Fourier series approximation of a sawtooth wave.

Cite As

Matt Tearle (2021). Simple real Fourier series approximation (https://www.mathworks.com/matlabcentral/fileexchange/31013-simple-real-fourier-series-approximation), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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