The search ends.. Finally an Excellent explanation of the concept with total clarity. Thanks a lot!

Clear voice, clear images, clearly explained. Thank you.

Thanks for the clarity of your explanations! I have to agree with other comments : you give the best lectures on signal analysis I've seen so far!

This is so clearly explained! Thank you!

You are one of the best in the KZfaq to explaining frequency. thank you for your effort

Thank you so much that was so clear !! We have hours of courses in university and still understand nothing, but here with a 10 min videos everything is cristal clear !! Wonderful job

You really made this easy, thank you. I was struggling with understanding these two domains but now the light is there.

Thank you very much for this extremely clear and helpful series of over 17 videos explaining the Fourier Transform from basic concepts. so super cool 😎

Thank you. I hope that conveys how much I appreciate you tutorials.

Thank you very much for providing a concise and informative explanation.

Great way to explain both the domains.

A nice explanation with most clear concept.

Thank you so much!! I was trying to find a source to understand the difference clearly. You are awesome! I appreciate.

Finally, a very clear explanation! Thank you for posting!

The best explaination I've seen of this so far.

Wonderful explanation, brief, clear and simple. Lot of thankss..

you r one of the top teacher ive met,now frequency domain is sooo clear ..iv searrch for many youtuber to make me understand it n i found none but only u sir.......people should watch your videos to clear thei concept......you r the first youtuber where i memories the channel name.......keep it up sir

Crystal clear explanation! Thank you

FINALLY UNDERSTOOD this basic concepts. well done. thank you

Wow..... What an explanation that is. Clear. Thanks a lot.

Sir you are born to be a teacher ! I have follow your courses in Udemy and they are wonderfull too!

Finally, I can stop my search on this topic bcos I've got it

Hi Mike, I hope you are well. Absolutely beautiful way to explain the process, very impressive. Keep up the good work

In under ten minutes, along with clear pictures and verbal descriptions, you have removed the mystery (to me) of understanding the how/why/what-is-it-useful-for of Fourier transforms. I also appreciated that on the last slide, you explained the three things a student must be familiar with to do Fourier analysis (sine wave, complex numbers, dot product), and showed how the three things are combined to reach the end goal of Fourier coefficients. Thank you, and I look forward to watching your videos as I self-educate!

i gotta tell you for doing this video that, you are the definition of "Inner peace", at this moment :)

Thank you, you are great on this subjects. keep educating us

Give this guy a medal!

Hi, I use wavelets and Hilbert transform methods to analyze sea wave data for my Ph.D. in oceanography. Your videos and your book are really helpful. Thanks for your work

Thanks, and it's so easy & simple!

I finally understand why FT is used!! Was really lost in my digital image processing course for a while. Thank you for such a spectacular explanation, you're amazing!

thank you ! easy to understand and visually striking !

Fantastic resources, thanks Mike!

Very well explained!

I am doing a math ia on this topic and this video is extremely helpful and easy to understand. Thank you so much

شكرا جزيلا لك thank you very much :)

EXCELLENT!!!

Wow! Excellent explanation!

Thank you, it help me here!

This is pure gold ❤

Thanks so much for this fantastic explanation :)

Thats what I was finding, thanks

thank for the clear explanation. i wonder how to interpret frequency domain in 2D. like image. each row in image can be interpreted like your explaination. but as we know that image contain many rows. how we can visualize frequency domain of many rows. in addition images have columns too. thank you

Amazing, thank you ;)

thank you for that's awesome video

Thank for such as great explanation!!

searched a lot with the physical revelance of frequency domain and the search ended here. Thanks

thanks Mike

Great Explanation :)

Thank you.

One More Question-- I am in a way to convert a random road load data to PSD graph for FEA simulation. Could you help me understand the physics involved to simplify the data in frequency domain. Also need to understand the role of Gaussian or PDF in the algorithm!

Thanks Mike this clearly explained . Can it happen Noise Amplitude starts dominating sinosodial waves meaning SNR

Thank you, I finally understood

nice ! please , if I want to create image from sampled signal ( sine wave for example ), how can get this please the image like white line and black line

THANK YOU

Can we say that: fourier transform is a crosscorellation of a time dependent function with sine or cosine function for different frequencies.

Very great explanation. How we can convert from the time domain to the frequency domain in MATLAB? I used the following code to convert data from time domain to frequency, but the plots in the frequency domain are totally different from what I see in this video and I can not get information from them. This is the code: %% Compute the Fast Fourier Transform FFT of the refrigerator dt=.001; n=length(ref(9906:31449)); fhat=fft(ref(9906:31449),n); % Compute the Fast Fourier Transform PSD=fhat.*conj(fhat)/n; %Power spectrum (power per frerquency) freq=1/(dt*n)*(0:n); %Create x-axis of frequencies in Hz L=1:floor(n/2); %Only plot the first half of freqs figure; plot(freq(L),PSD(L)) title('FFT')

Finaly i understand it thhhaaaaaannnnkkkkkk uuuuu ssssooooooo muchhhhhhhhhh u r a hero

Thanks bro for this awesome vedio

It was so beneficial to me, and the explains were so clear, but you pointed out why the amplitude is half of the distance between throughs and the peaks. Could you please explain that?

finally I know what these frequency graphs tell...

thank you

I'm your big fan

That was excellent

cleared all my doubts sir:)

Nice way presented the Noise, which i struggled before to understand. One Question... 1. In nose induced signal, time domain max amplitude goes to ~5. But frequency domain is 1. Could you clarify plz?

That was purly ı was looking for .

Thanks br0😁

AT 3:50 when you say its difficult, yet possible to figure out the frequency components from the time graph, can you help how you would figure that out?

Mr., where r u all these time?

Thanks wow

Search ends

Thank u so much it was really helpful 😇

Cristal Clear

I want the code

🙏🙏🌹🌹

i love you

In the second example, the amplitude must be 5 not 1

Thank you.