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[docu] gifs that explain deconvolution intuitively #72
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Animation: Good idea. But I only see a blank .PNG graphic without content above. |
Should be a bit slower but else I think its fine for 1. I think I will not add noise to this, but I can already see the slide freezing at the last frame and removing the ERPs and then asking how we can recover it. Then look at 2-3 points at similar \tau and see that the overlap with other trials is different to get an intuition of how deconvolution can potentially work. The other gifs are still to be made though |
Too large for github... https://benediktehinger.de/upload/unfold_explanation_v2.gif <-- direct link |
nice. some minor suggestions: animation 1:
animation 2:
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yeah the function ranges, I'm still not sure what to do. The first one is over the whole experiment "70s max", the second one shows that the distance between events is increased (because the number of events is fixed at 50.) True response would add yet another panel, I feel I always have too many panels already :-D Also unfold erp is identical to the true one. Will fix the other things after I finished the nonlinear explanation figure |
Non-linear graph. There is still a mistake in the second column, because the true effect is not visible. I will drop many of the ticklabels, maybe change the scale between first, and second+third column for the difference But okay, my daughter is awake :P no more giffing for now. Thanks for your feedback! |
First one too large again https://benediktehinger.de/upload/unfold_explanation_v3.gif |
I'm thinking of a series of gifs that explain convolution / deconvolution
Event "spikes" convolved with a simple ERP-like pattern => + add continuous noise
Estimate two ERPs and change overlap (show % overlap for each)
Unfold Estimate in Relation to number of events, compare to ERP (should be more or less identical except shape differences)
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