The Fast Fourier Transform Algorithm
Here I discuss the Fast Fourier Transform (FFT) algorithm, one of the most important algorithms of all time.
Book Website: databookuw.com
Book PDF: databookuw.com/databook.pdf
These lectures follow Chapter 2 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz
Amazon: www.amazon.com/Data-Driven-Sc...
Brunton Website: eigensteve.com
This video was produced at the University of Washington
Пікірлер: 95
did anyone else realize how well this guy can write backwards?
Your central matrix factorization is not quite right. The top two blocks should be [I_{512}, D_{512}] instead of [I_{512}, -D_{512}] . Looks like the same error is in your databook.pdf.
Before I understand FFT, I want to understand how he's writing mirrored so effortlessly.
The only thing I can't wrap my head around is how he is writing everything backwards.
Sir u missed 6...😂😂
0,2,4,6; not 8
Why Transform not found.. I dont understan english language
Such an elegant method using divide and conquer :)
I recommend your channel to my friends when they asked me to explain how FFT works. Great channel!!!!! Keep up the good work professor!!!
This is really an engineering video. It doesn't use or show why something is true in theory, but just shows how it works, not WHY it works
Steve, I've just paraphrased (and sourced) this video in my final report for my MSc project.
Thank you for sharing, Steve Brunton. This is great lecture!
I also recommend reading "Numerical Recipes" in C or Fortran, it explains this algorithm from a computer scientist's perspective.
beautiful lectures that inspire a desire to learn. Your work is much appreciated, thanks!
A notion of prof. Strang is always a good sign.
Great lecture! Understand clearly. Thanks👍
I can confidently say that this is a great channel. I liked every video. Many Thanks.
Simply Wow!!
Hate to say it, but my signal processing class is nothing like this. My professor only goes over the math parts and nothing more. He doesn't even mention how any of it is used to process signals. So thank you for actually putting the SIGNAL in SIGNAL PROCESSING.
Very informative lecture, learned a lot from it. However, at