Time and frequency domains 

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!

Mike Cohen and Mark Newman. The saving graces of any learner. Good stuff mister 👍🏻👍🏻.

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

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

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

This is so clearly explained! Thank you!

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

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

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

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 😎

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!

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

Finally, a clear explanation. Thank you!

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

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

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

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, this is the explanation im looking for quite sometime.

FINALLY UNDERSTOOD this basic concepts. well done. thank you

Give this guy a medal!

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

Thank you for the clear explanation!!!

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

Great way to explain both the domains.

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

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

thank you for such a great and informative video!

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

Wow! Excellent explanation!

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

thank you ! easy to understand and visually striking !

A nice explanation with most clear concept.

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

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

Thanks, and it's so easy & simple!

Crystal clear explanation! Thank you

Thank for such as great explanation!!

Fantastic resources, thanks Mike!

شكرا جزيلا لك thank you very much :)

EXCELLENT!!!

Thank you, it help me here!

finally I know what these frequency graphs tell...

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?

This is pure gold ❤

Very well explained!

Thanks so much for this fantastic explanation :)

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

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

Thank you, I finally understood

Great Explanation :)

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')

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

Thats what I was finding, thanks

hi, is there a difference in sound? i saw ifi ad from their dongle, instead of frequency domain they manipulate the time domain. sorry i don't understand any of your explanation(i am on health sector). thank you if you ever read and answer this.

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?

Thank you.

why do you count the picks and not the periodes of the signals ? thank you for the videos

thanks Mike

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

thank you

thank you for that's awesome video

That was purly ı was looking for .

Amazing, thank you ;)

cleared all my doubts sir:)

I'm your big fan

Mr., where r u all these time?

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

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!

Search ends

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

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?

That was excellent

Thank u so much it was really helpful 😇

Thanks br0😁

Thanks wow

Cristal Clear

I want the code

i love you

🙏🙏🌹🌹

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

THANK YOU

Thank you.