Convolution why reverse

It may not display this or other websites correctly. You should upgrade or use an alternative browser. Time reversal of a signal in convolution. Thread starter Ershadh Start date Jul 14, Status Not open for further replies. Ershadh Junior Member level 1.

While performing convolution of two signals why do we time reverse one of the signals? What would happen if we do not time reverse one of these?

This is answered in another domain. Any function or signal can be expressed in time or frequency domain. When you do the multiplication operation between two such signals it is same as doing the convolution operation in the other domain. Consider two signals f t and g t in time domain. If you need the convolution of both i. Instead you can do the multiplication of F w and G w which are the fourier transforms of the signals f t and g t respectively.

Keep in mind though, that this only sounds bad when "t" corresponds to "time". Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. What does it mean by deconvolution backwards convolution? Ask Question. Asked 5 years, 4 months ago. Active 1 year, 2 months ago. Viewed 6k times.

What does it mean by deconvolution or backwards convolution in convolutional neural nets? Improve this question. Add a comment. Active Oldest Votes. A detailed explanation is well beyond the scope of StackOverflow; this is not a tutorial site. Improve this answer. Prune Prune I'd like to add a resource that I have found to be very helpful to understand deconvolution also called transposed convolution.

In the 4th section of this paper arxiv. This answer is wrong of misleading. Accepted Answer. Matt J on 2 May Vote 1. Cancel Copy to Clipboard. Edited: Matt J on 2 May It's not meant to be a "benefit" or to avoid disastrous consequences. It's meant to be a definition.

If you don't flip, then you violate the agreed upon definition of convolution. Convolution without the flip has a name of its own: correlation.

What motivated people to define convolution with a flip? Well in 1D, it means, for example that the convolution of causal signals will also be causal.

Also, when you flip, then the convolution with an impulse response function of a system gives you the response of that system. If you don't flip, the response comes out backwards. Why do the same in 2D? Using a different definition in 2D would make it inconsistent with 1D. And btw. IA: Wouldn't flipping symmetric kernels simply take more calculations, e. Image Analyst on 2 May The time to flip in so miniscule it's inconsequential. If you go through the theory linear systems theory you'll understand.

If you want to understand the causality, imagine a filter that's a right triangle, with the small pointy end on the left and the steep edge on the right.

Now shift that past a delta function. If you don't flip and just start shifting your filter past it will hit the tall steep edge first and then ramp down. So then your response is opposite to your filter, but they must be the same if it's a delta function.

Basically it's because time goes along the x axis with the small time values on the left and the big later time values on the right. So if you start shifting in, you're having the big time values hit your signal first, which is not right causal. So you have to flip it to make the small time values shift in first. Not sure if that's such a great explanation but it's what I offer just off the top of my head.