It is so crazy that Gauss discovered a lot of things in mathematics that took people hundreds of years to realize.

I was just watching this but I kept being distracted and impressed by the fact that you are writing backwards. :O

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.

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.

did my man just casually write on the board backwards for us to see it in the correct orientation? Because that's impressive

Easily one of the best instructional videos on KZfaq, 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 !

Are we not going to talk about how well this guy writes backwards? 🖊

The best lecture series I've seen in KZfaq. Thanks a lot for everything.

No words to express my gratitude for this awesome content

Please Prof. Steve Brunton kindly we need video lectures on the wavelet transform , DWT , CWT , etc , thanks and best regards

This format is simply the best.

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.

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.

the best series I came across recently

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.

Concepts simplified to the very core. Thank you for the lecture series!

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.

Your Videos are So awesome and wonderfully high quality!

Thank you so much, I am so excited to learn when I watch your videos!

Amazing Prof Brunton.

Professor, please tell me how can I monetarily support you. The contents you created are beyond brilliant!

Thank you so much for these very clear explanations! They are really helpful

I wish I could be your student in my uni life 😭 you explained what I need to grasp

Thanks from the lecture! from Japan

Thanks you really rock and you’re a great story teller!!

Steve ,you are the best .

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

thank u for prompt reply. Be Well !

Can't wait to watch the next video...i really love your work

beautiful video - very well explained

Wow did this just make me understand scaling the dow Jones day trading ? Very useful information! I wish this guy was my personal teacher!

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!

Great video! Thank you!

really high quality info, thnx.

how does he write backwards so well ???

8 minutes for NOT describing the FFT

Fantastic! What system did u use to produce the lecture?

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 🙃

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.

Obrigado, professor, por nos explicar o porque de usar o FFT (n x long) ao invés do DFT( n x n).

Dear Prof. Brunton, is FFT mostly used for simple domains problems? (FEM, FVM, Meshless, etc)

if I plot the spectral where the X axis is time, do I have to IFFT first? thank you

Where were you all my college life?

awesome, thanks!

you are too brave keep going!!

Holy shit. Thank you. Thank you so much.

Do you plan to explain the algorithm and the math behind it? Trying to write this algorithm for a compute shader

very good

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?

God bless you!

Are ‘Private Vids’ available under your Membership Plan ?

awesome

Thank you so much for explaining complex thing really Easy way! Can you do this for "Homomorphic Encryption" too??

Amazing explanation! But what I couldn't wrap my head around is how can he write backwards so casually ?!

Sparsity and Compression is a private video... is a part of any membership plan?

Ông này viết ngược luôn ghê vch :)) respect!

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

awesome video and explanation.... how the heck are you writing backwards??

Ok thank you :)

please help me with this, why for a 10 sec audio, n=4.4x 1000000. what basically 'n' is?

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.

When we say O(nlog(n)) isn't the log base 2? so in the case where n = 1000, log(n) ~= 10 not 3?

T-Pain owes his career to FFT

Gauß was majorly underestimating his own work

FFT, how about that FHT (Fast Handwriting Transform)??? Can you reveal that algorithm?

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.

Karl Friedrich Gauss must have been, no doubt, one of the smartest men who ever walked the earth. Absolute genius.

Hardware is the physics. Software is the math.

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?

I thought the complexity of FFT was n*log2(n) not with a base of 10?

So this is just an introduction of FFT? Well I was hoping for learning the details and implementation.

idek what ur talking about but nice video!

Isn't it O(n(n+1))?

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

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