Deconvolution with Python in real life

1. What is deconvolution used for?
2. How do you Deconvolve in Python?
3. What is deconvolution in signal processing?

What is deconvolution used for?

Deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data. An easier method of deconvolution involves the use of derivative spectroscopy or derivative analysis.

How do you Deconvolve in Python?

The deconvolution has n = len(signal) - len(gauss) + 1 points. So in order to let it also reside on the same original array shape we need to expand it by s = (len(signal)-n)/2 on both sides.

What is deconvolution in signal processing?

Deconvolution is the process of filtering a signal to compensate for an undesired convolution. The goal of deconvolution is to recreate the signal as it existed before the convolution took place. This usually requires the characteristics of the convolution (i.e., the impulse or frequency response) to be known.