- #1
Gonzolo
Hi. I have a data gaussian g(t) and data that I suspect is a convolution (g*f). I want to find f(t), so I need to deconvolute (using Origin preferably).
If I convolute [tex]g*g[/tex], I get something very beautiful.
If I convolute [tex](g*f)*(g*f)[/tex], I get something very beautiful.
If I deconvolute [tex]g*^-^1g[/tex], I get something very beautiful.
If I deconvolute [tex](g*f)*^-^1(g*f)[/tex], I get something very beautiful.
If I convolute [tex]g*(g*f)[/tex], I get something acceptably beautiful.
But why is it that when I deconvolute [tex](g*f)*^-^1g[/tex], which should recover the f I'm looking for, I get the most horrible noise graph I've ever seen? Roughly a very thick (zigzag) useless straight line. How do I recover f with minimal noise?
Edited with Latex notation after first reply
If I convolute [tex]g*g[/tex], I get something very beautiful.
If I convolute [tex](g*f)*(g*f)[/tex], I get something very beautiful.
If I deconvolute [tex]g*^-^1g[/tex], I get something very beautiful.
If I deconvolute [tex](g*f)*^-^1(g*f)[/tex], I get something very beautiful.
If I convolute [tex]g*(g*f)[/tex], I get something acceptably beautiful.
But why is it that when I deconvolute [tex](g*f)*^-^1g[/tex], which should recover the f I'm looking for, I get the most horrible noise graph I've ever seen? Roughly a very thick (zigzag) useless straight line. How do I recover f with minimal noise?
Edited with Latex notation after first reply
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