Это видео недоступно.
Сожалеем об этом.
The Fast Fourier Transform (FFT)
HTML-код
- Опубликовано: 30 мар 2020
- Here I introduce the Fast Fourier Transform (FFT), which is how we compute the Fourier Transform on a computer. The FFT is 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
It is so crazy that Gauss discovered a lot of things in mathematics that took people hundreds of years to realize.
Makes you wonder how many people have ideas that could change the world, but choose not to share them because they don't see their full potential (or they assume someone else has already had that idea).
Fun fact 101: when something is not named after Gauss is because somebody rediscovered it later or it would be confusing as everything is already named after him. Probably the latter though.
@@nameismetatoo4591 i think its far more interesting to think how many people could have potentially had great ideas but were just exploited working class people who never had the opportunity to actually form their intellect and study something
@@nameismetatoo4591 Reminds me of the newton-leibniz calculus controversy.
Heavy Gauss Rifle
This is what online lectures should be like. Thank you very much Dr. Brunton for sharing these lectures. I can't emphasise enough how amazingly done these are.
I was just watching this but I kept being distracted and impressed by the fact that you are writing backwards. :O
Ahahaha same here XD
Same here , you wrote them so naturally without any hesitation
He isn't. The video is mirrored.
He isn't writing it backwards, there is very easy, logical explanation. This has been mirrored, and if you look closely you can see that he has a ring on what would be his right hand, which isn't right, usually rings are on left hand.
they are not writing backwards.Its a simple use of technology. There is an MIT page explaining how they do it, so others can copy it. There are tons of resources that explains how to build that too.its cool!
The best lecture series I've seen in RUclips. Thanks a lot for everything.
Easily one of the best instructional videos on RUclips, the clarity in your articulation of the concepts makes the otherwise murky subject so much more approachable. Can't applaud you enough for putting these videos togather. Cheers !
This lecture was like a trailer to the actual one (which I assume comes later in the series). He didn't actually do anything here.
Very well produced - thank you Steve for this excellent lecture ! FFT is truly what drives the World today... and into the future - with endless applications, in the physical sciences astro, aviation, and medical world.
This format is simply the best.
This content is amazing, thank you so much for posting this. I knew how to compute a fourier transform of on a defined function but was incredibly confused how computers did it on the sample data they create from analog signals. I had no idea you could do it to discrete data.
Thank you so much, I am so excited to learn when I watch your videos!
You are so welcome!
Your Videos are So awesome and wonderfully high quality!
Thank you so much for these very clear explanations! They are really helpful
Concepts simplified to the very core. Thank you for the lecture series!
You're welcome!
Thanks you really rock and you’re a great story teller!!
Thank you so much for making this course publicly available professor!
Your approach to teaching Fourier Analysis manages to provide a level of intuition on the subject that makes the equations themselves seem much less daunting.
Also the anecdotes and stories you weave into this course are pretty much the icing on the cake.
I wish there were more black people in Science and mathematics
Amazing Prof Brunton.
the best series I came across recently
Are we not going to talk about how well this guy writes backwards? 🖊
He writes regularly and the video is mirrored ;)
@@marcnassif2822 Ha. Seems I didn't give that any thought because I _wanted_ it to be true! 😋
@@marcnassif2822 Is he left handed then?
@@akhilezai His handwriting is way too neat for him to be left handed haha, but yes he is left handed.
beautiful video - very well explained
Please Prof. Steve Brunton
kindly we need video lectures on the wavelet transform , DWT , CWT , etc , thanks and best regards
Thanks from the lecture!
from Japan
Your welcome from Seattle!
Can't wait to watch the next video...i really love your work
Awesome! Next one should be out on Saturday.
@@Eigensteve Can't wait till Saturday..😄..haven't found any good content on fft algorithm on RUclips..really looking forward to it
No words to express my gratitude for this awesome content
really high quality info, thnx.
did my man just casually write on the board backwards for us to see it in the correct orientation? Because that's impressive
Steve ,you are the best .
Great video! Thank you!
An important point I missed in the video is the Kronecker property for the multivariate case. This enables the use of many 1-dimensional operations instead of one N-dimensional operation. Also called "vec-trick" on tensorproduct elements.
Professor, please tell me how can I monetarily support you. The contents you created are beyond brilliant!
I think buying his book might be a very good idea.
thank u for prompt reply. Be Well !
Wow! This is an awesome explanation! Down to earth, straight forward, excellent! BTW - you are quickly, and legibly writing backwards like some kind of Leonardo DaVinci !! What the heck! Incredible!
Hey David Cardin, do you like listening to songs by Imagine dragons ?
In addition to satellite TV, it is cool that the new digital Terrestrial TV broadcasting standard ATSC 3.0, which has just commenced in US also uses OFDM-based modulation and consequently requires FFT blocks on the receiver side and iFFT on the transmitter.
I wish I could be your student in my uni life 😭 you explained what I need to grasp
Wow did this just make me understand scaling the dow Jones day trading ? Very useful information! I wish this guy was my personal teacher!
if I plot the spectral where the X axis is time, do I have to IFFT first? thank you
awesome, thanks!
how does he write backwards so well ???
maybe the video is inverted . He writes normal and then they invert it using software
@@dzemper9410 If he's writing normal then the inversion would be backwards
@@jd87a but the camera sees from behind the board, so inverting again in software will put it correctly
You can search on Lightboard or Lightboard Studio (either of those names) to see more on how this works!
Left handed and the image is inverted.
It is so crazy that Steve wrote every notes from the back, which means every characters and graphs he is writing should be flipped along y axis by 180 degrees
you are too brave keep going!!
8 minutes for NOT describing the FFT
Holy shit. Thank you. Thank you so much.
Fantastic! What system did u use to produce the lecture?
Obrigado, professor, por nos explicar o porque de usar o FFT (n x long) ao invés do DFT( n x n).
De nada
Brs everywhere.
Um abraço
Do you plan to explain the algorithm and the math behind it? Trying to write this algorithm for a compute shader
Yes, I believe it will come out on Saturday.
Dear Prof. Brunton, is FFT mostly used for simple domains problems? (FEM, FVM, Meshless, etc)
very good
God bless you!
Thank you so much for explaining complex thing really Easy way!
Can you do this for "Homomorphic Encryption" too??
I'm by no means an expert in encryption, but that would be a fun series.
Are ‘Private Vids’ available under your Membership Plan ?
Sorry about that... that video should be coming out at the very end of this series on FFT, in about a month. Stay tuned!
awesome
a) What is this FFT image called in general? (b) What kind of information can you obtain from the FFT image? (c) Is this same as an electron diffraction pattern?
bruh
please help me with this, why for a 10 sec audio, n=4.4x 1000000. what basically 'n' is?
Where were you all my college life?
Sparsity and Compression is a private video... is a part of any membership plan?
Sorry about that... that video should be coming out at the very end of this series on FFT, in about a month. Stay tuned!
I never understand how you do your videos. How the heck do you write in the air, and how you this invisible board trick. Please explain
When we say O(nlog(n)) isn't the log base 2? so in the case where n = 1000, log(n) ~= 10 not 3?
I guess it doesn't matter as much in big O notation because it only conveys a general trend while omitting most of the less significant factors. But yes, Cooley-Tukey FFT is O(n*log_2(n))
awesome video and explanation.... how the heck are you writing backwards??
I was wondering who invented FFT so I went to wikipedia, letting the video continue to play while I tuned it out to read. When I tuned back into the video, you were just finishing explaining exactly that. Oops 🙃
Nice :)
Amazing explanation! But what I couldn't wrap my head around is how can he write backwards so casually ?!
oh video is inversed on X axis! great move 😉
what does PDE stand for???????
I think in the N Log N, the base is not 10 as mentioned here at 3:30. I think the base should be 2.
I think I agree.
Ok thank you :)
Ông này viết ngược luôn ghê vch :)) respect!
FFT, how about that FHT (Fast Handwriting Transform)??? Can you reveal that algorithm?
probably called mirroring or vertical inversion of video :D
T-Pain owes his career to FFT
Isn't it O(n(n+1))?
Gauß was majorly underestimating his own work
I thought the complexity of FFT was n*log2(n) not with a base of 10?
You can go between log in any bases by multiplying with a constant. So log2(n) = log2(10)*log10(n)
@@Eigensteve but you have no constant in front of the log(n) term in the video. Is the constant just ignored because it is a complexity formula?
@@ceeb830 That's right, we usually drop the constant, since we are just interested in how the trend scales for large n
So he's left handed, can you figure out how I figured it out?
If you can right in reverse, you can explain the Fourier transform.
So this is just an introduction of FFT? Well I was hoping for learning the details and implementation.
Never mind. Found the next video
idek what ur talking about but nice video!
Karl Friedrich Gauss must have been, no doubt, one of the smartest men who ever walked the earth. Absolute genius.
Did he really write mirrored on glass better than I write normal on paper?
That's logN base 2, not base 10. So for n=1000 we'd get logN = 10
@Michael Smith I don't have an idea what you're talking about?!
I just recently read a paper that it's actually faster to just compute the DFT if you're using GPU acceleration, since matrix multiplication is inherently more parallel despite vendors actually providing their own optimized FFT libraries. The performance benefit of DFT is even greater the larger the input compared to the optimized FFT library.
The paper is:
Davuluru, Venkata Salini Priyamvada; Hettiarachchi, Don Lahiru Nirmal; Balster, Eric (2022): Performance Analysis of DFT and FFT Algorithms on Modern GPUs. TechRxiv.
I was watching a video of a kid drinking a bottle of Gatorade through a toilet paper roll straw. How did I end up here?
Hardware is the physics. Software is the math.
Gauss was a freak
bff2873
fft batch
Left handed
Don’t watch. He doesn’t explain the FFT.
Please Prof. Steve Brunton
kindly we need video lectures on the wavelet transform , DWT , CWT , etc , thanks and best regards
Coming up soon!