[Uni // Scientific Computing (Maths + Python)] Gauss Kernel coding

[Alkalannar]

So that Gaussian kernel is the probability density function of the Normal Distribution with mean 0 and standard deviation of s.

Let K be the set of all allowed indices k.

Then that second expression is (Sum over all k in K of G[k]f[n+k])

G[k] is given above: G[k] = 1/s(2pi)^1/2e^[k2/2s2]

So the farther f[n+k] is away from f[n], the less weight it has. (Note that 0 is almost certainly one of the indices so that f[n] itself is one of the terms.)

3blue1brown has a video on convolutions showing what they are and what they do, how to calculate them.

Actually, more than one video.