I ran a finite-difference simulation and the behavior of an output signal, $s$, in time, $t$ (sampled with period $\Delta t$) behaves approximately as in the figure below. It is well-described by a slowly-varying pulse plus a rapidly oscillating signal of the same envelope with lower amplitude.

signal with noise

For concreteness, I computed this sample signal in MATLAB with the following code.

f_noise = 20;
t = linspace(-4,4,2e3);
signal = exp(-t.^2);
noise = 0.25*exp(-t.^2).*sin(2*pi*f_noise*t);
signal_w_noise = signal + noise;

I emphasize that this is just a sample signal and not the actual data I want to analyze.

I wish to compute the "time-average" of the signal. By this I mean the signal without the rapidly oscillating component (which we could call noise). To get a clear picture of the problem, I calculated the Fourier transform of the signal approximately using MATLAB's fft function and obtained the spectra below.

spectra of signal and signal with noise

From this plot, I suspect a notch-filter could do the trick. However, I know very little of signal processing and I know how to use first-order filters from undergraduate electric-circuit courses. What is a simple to use but effective notch-filter I could use? I am particularly looking for the transfer function in the frequency domain of such notch-filter, because the software I use to generate the data is equipped with a FFT algorithm, so I'd like to do the processing there and avoid exporting the whole data to, say, MATLAB.

  • 3
    $\begingroup$ you can get a simple and effective second-order IIR notch filter from this. sorry i haven't done a pdf copy with decent math markup. i dunno why i haven't. $\endgroup$ Commented Oct 19, 2017 at 3:28
  • $\begingroup$ Using a notch filter means that you know the frequency of your noise. If that is the case, why don't you give us a little more detail about your application, maybe it could help propose a better solution than the notch filter. $\endgroup$ Commented Nov 19, 2017 at 3:21
  • $\begingroup$ Could you share the signal samples? $\endgroup$
    – Royi
    Commented May 18, 2018 at 5:09

2 Answers 2


i might also recommend a low-pass filter over a notch filter unless the OP is absolutely certain, in advance, what the frequency of the "noise" is. if the OP has less information about the high-frequency noise that the OP desires to remove (leaving the moving average), then a LPF with DC gain of 1 (or 0 dB) and a cutoff frequency lower than the lowest expected frequency component in the noise is indicated. not a notch filter.

whether it's a Kaiser-windowed-sinc FIR or an IIR LPF (perhaps a simple 2nd-order IIR suffices) is a design and performance issue.

but i would not recommend a notch unless it is known apriori that the "noise" is sinusoidal and what the frequency of the sinusoidal "noise" is.


I would suggest that you use a lowpass filter rather than a notch filter to filter out the noise (assuming the signal is slow varying with respect to noise as mentioned). Use a FIR low pass filter designed by Kaiser Window Method (Ref: Chapter 7, Discrete Time Signal Processing, Alan V. Oppenheim, Third Edition)

  • $\begingroup$ Why Kaiser? Why not any other window? Why windowed and not optimum, or adaptive, or...? Why not IIR? Why not a blunt passive RLC? $\endgroup$ Commented Dec 19, 2017 at 7:14

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