The following scripts use Octave's Signal Processing Toolbox; If you don't have the toolbox installed, get it from Octave-Forge.
It is easy to design a low pass filter:
% Nyquist frequency, [Hz]
% The Nyquist frequency is half your sampling frequency.
Fnyq = 1500/2;
% The cut-off frequency of your Low pass filter. Note that this filter must be greater than 0 and less than Fnyq
Fc=1/4; %[Hz]
% Create a first-order Butterworth low pass
[b,a]=butter(2, Fc/Fnyq);
% clear unused variables
clear("Fnyq", "Fc");
Now let's test the filter. First, let's generate a input signal containing components at 1Hz, 10Hz and Gaussian white noise.
% Create a 5 seconds signal with 3 components: % a 1Hz omponent, a 200Hz sinusoidal component and some gaussian noise. t=0:1/1500:5; input=sin(2*pi*t) + sin(2*pi*200*t) + rand(size(t)); % Apply the filter to the input signal and plot input and output. output=filter(b,a,input); plot(t, [input; output])
You can also compare the input and outout signals in the frequency domain:
plot([abs(fft(input)); abs(fft(output))]) find(abs(fft(input)) > 3000) find(abs(fft(output)) > 3000)