I had this question after seeing that polynomial regressions fit polynomial functions of different degrees to a time-series, since the mean of a time series is a constant and that a constant is also a polynomial of degree 0 i wondered if the SG filter who also fit polynomial functions to a signal over a period window can be called a moving average.

So is it correct to say that a Savitsky-Golay Filter that try to fit a polynomial of order 0 to a signal is considered a moving average filter ?


1 Answer 1


Yes you can consider a zeroth (or first) order SG filter as a moving average filter. Below MATLAB / Octave code computes the impulse response of a SG filter of order $N$ and length $2M+1$ :

% Savitzky-Golay Filter
clc; clear all; close all;

N = 0;                      % a0,a1,...,aN : Nth order polynomial
M = 3;                      % x[-M],...,x[M] : 2M + 1 data

A = zeros(2*M+1,N+1);
for n = -M:M
    A(n+M+1,:) = n.^[0:N];

H = (A'*A)^(-1)* A';        % LSE fit matrix

h = H(1,:);                 % S-G filter impulse response (non-causal symmetric FIR)

title(['Impulse response h[n] of Savitzky-Golay filter of order N = ' num2str(N), ' and window size 2M+1 =  ' , num2str(2*M+1)]);

plot(linspace(-1,1,1024), abs(fftshift(fft(h,1024))));
title('Frequency response magnitude of h[n]');

figure,plot(linspace(-1,1,1024), 20*log10(abs(fftshift(fft(h,1024)))));
title('Frequency response magnitude of h[n]');

The impulse response for $N=0$ is :

enter image description here

as can be seen, it's a moving average (constant) impulse response.


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