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Can some please explain this equation in brainlet terms? My brain

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Can some please explain this equation in brainlet terms? My brain just shuts down whenever I see math with summation signs

Green text explanations appreciated
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>>9140826
What do you not understand?
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>>9140826

sum of the pointwise multiplication of one signal and the reversed, shifted (by n) version of another.
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>>9140826

>He doesn't exclusively use Einstein notation
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Probably exists in a code library somewhere anyways desu. But it would be nice to understand this stuff.
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My dads room used to be like this. He has a bachelors in comp sci from a university at DC, and has been coding for almost 40 years.
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>>9141004
But he had a whole wall filled up with monitors/towers.
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>>9140831

basically the equation in its entirety.

I don't understand the summation sign, the limits to +/- infinity and those square brackets. Also don't understand what a, v, n and m mean
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So, I recently visited a lecture about convolution (that was part of a bigger event) in sound. I'm pretty new to these fields but from seeing Fourier mentioned in the text I am correct to assume that this is the same principle as the one in sound engineering?
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>>9140826
>implying /sci/ understands science or math on any practically applicable level
best green text advice one can get. try somewhere else.
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>>9140826
Consider f(x) = x^2 + 3x + 7 and g(x) = x^3 + x^2 + 7x + 9. Now multiply them to get h(x) which will obviously be another polynomial. Say you want the coefficient of x^3 in h(x). Take the 7 from f(x) and x^3 from g(x) and multiply them to get 7x^3. Take 3x from f(x) and multiply with x^2 from g(x) to get 3x^3. Take x^2 from f(x) and multiply it with 7x in g(x) to get 7x^3. So the coefficient of x^3 in h(x) will be 7 + 3 + 7 = 17. If you let A(k) denote the coefficient of x^k in a polynomial a(x), you can see that we've just computed H(3) to be F(0)G(3) + F(1)G(2) + F(2)G(1). Which is just the convolution of F and G. Now do the same with an infinity of coefficients.
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https://en.wikipedia.org/wiki/Convolution#Visual_explanation

Convolution is a pain in the ass except for when you're working with a few functions like deltas.
Thread posts: 12
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