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In the Laplace transform domain, the Laplace transform of the output is the Laplace transform of the impulse response times the Laplace transform of the input.
And so this is the Laplace transform of the first.
That's the Laplace transform of the error signal.
Compute the fast fourier transform of the source data vector.
In other words, the Fourier transform of the output is j omega times the Fourier transform of the input.
Next, the Fourier transform of the measured data is calculated.
Well, we know that the Fourier transform of the output is the Fourier transform of the input times the Fourier transform of the impulse response of the system, namely the frequency response.
So in the frequency domain then, the Fourier transform of the sampled signal, which is an impulse train, is the convolution of the Fourier transform of the sampling function P of t and the Fourier transform of the sampled signal.
So the Fourier transform of the output is 1 over j omega plus a times the Fourier transform of the input.
And in the frequency domain, we have, again, the Fourier transform of the original sequence and we have the Fourier transform of the sampled sequence.
At this point, we can recognize that here the Fourier transform of the output is the product of the Fourier transform of the input and some complex function.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com