Understanding Convolution: From Discrete to Continuous Applications

Discrete convolutions, from probability to image processing and FFTs. Video on the continuous case: https://youtu.be/IaSGqQa5O-M Help fund future projects: https://www.patreon.com/3blue1brown Special thanks to these supporters: https://3b1b.co/lessons/convolutions#thanks An equally valuable form of support is to simply share the videos. Other videos I referenced Live lecture on image convolutions for the MIT Julia lab https://youtu.be/8rrHTtUzyZA Lecture on Discrete Fourier Transforms https://youtu.be/g8RkArhtCc4 Reducible video on FFTs https://youtu.be/h7apO7q16V0 Veritasium video on FFTs https://youtu.be/nmgFG7PUHfo A small correction for the integer multiplication algorithm mentioned at the end. A “straightforward” application of FFT results in a runtime of O(N * log(n) log(log(n)) ). That log(log(n)) term is tiny, but it is only recently in 2019, Harvey and van der Hoeven found an algorithm that removed that log(log(n)) term. Another small correction at 17:00. I describe O(N^2) as meaning "the number of operations needed scales with N^2". However, this is technically what Theta(N^2) would mean. O(N^2) would mean that the number of operations needed is at most constant times N^2, in particular, it includes algorithms whose runtimes don't actually have any N^2 term, but which are bounded by it. The distinction doesn't matter in this case, since there is an explicit N^2 term. Thanks to these viewers for their contributions to translations Hebrew: Omer Tuchfeld Italian: Emanuele Vezzoli Vietnamese: lkhphuc -------- These animations are largely made using a custom python library, manim. See the FAQ comments here: https://www.3blue1brown.com/faq#manim https://github.com/3b1b/manim https://github.com/ManimCommunity/manim/ You can find code for specific videos and projects here: https://github.com/3b1b/videos/ Music by Vincent Rubinetti. https://www.vincentrubinetti.com/ Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown Stream the music on Spotify: https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u Timestamps 0:00 - Where do convolutions show up? 2:07 - Add two random variables 6:28 - A simple example 7:25 - Moving averages 8:32 - Image processing 13:42 - Measuring runtime 14:40 - Polynomial multiplication 18:10 - Speeding up with FFTs 21:22 - Concluding thoughts ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe: http://3b1b.co/subscribe Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3blue1brown Reddit: https://www.reddit.com/r/3blue1brown Instagram: https://www.instagram.com/3blue1brown Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brown