Frequency domain - tutorial 6: Fourier transform tables
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- čas přidán 23. 08. 2024
- In this video, we learn about Fourier transform tables which enable us to quickly travel from time to the frequency domain. The main learning objective is to fully understand table of pairs
and table of properties (please don't memorize these tables)!
Learn Signal Processing 101 in 31 lectures covering time, frequency and Laplace domain in about 8 hours all together:
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References:
[1] Alan V. Oppenheim, Alan S. Willsky, S. Hamid Nawab, Signal & Systems, 2nd Edition, Prentice-Hall, NJ, USA, 1996.
[2] Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, 3rd Edition, Prentice-Hall, 2009.
[3] Michael D. Adams, Continuous-Time Signals and Systems, University of Victoria, Canada, 2013.
Free textbook and lectures (courtesy of Dr. Michael Adams):
Link to the Dr. Adams' textbook: bit.ly/37rkwDC
Link to the Dr. Adams' lecture slides: bit.ly/2WrwHKy
These videos are a Godsend! I have been struggling through this material all semester and am finally starting to understand it and see connections!!!!
Thank you very much and it's a great pleasure to help. Cheers!
Thanks, learnt some of this stuff but had no idea what I was doing with it in my current course. This is a great summary contained into a single video that explains the relationship between the standard tranform equations and the table pairs really well. Only dissapointed I didn't find this earlier.
Glad it was helpful!
Very promising video. I not at all felt bored anywhere. Very useful. I would like to see some videos on solving Convolution integrals, sampling, windowing techniques, Green's function. I understand it's tricky to cover all, but would be appreciable if you do it. Thank you so much.
Thank you very much. Please check www.sphackswithiman.com to see more videos. cheers!
Thanks sir
I'm as student at the Algerian IEEE and i really appreciate this lectures and i found them pretty helpful
It is a great pleasure to help, Aissa!
why didn't you share this with us earlier ya Aisaa why
@@bayarebouh2172 go check my post i explained this point in the notes
@@AissaAzzaz Duuh, I was joking
ياخو هادو ماذابيا نقراهم؟ أنا نقرا تيليكوم!
Absolutely fantastic. Best explanation on CZcams. Big thumbs up!
Thanks a lot, my friend. I am very happy that you find this video useful. Cheers!
thank you man! you make all complexity easy! خوشم اومد دمت گرم. ترکوندی
hahaaaa, thanks a lot dooste aziz ;)
You, Sir, are awesome, Great video. Thank you
mahsa tahmouresi thanks Mahsa jan ;)
Omg thank you soo much!!totally understood everything
I hope i can pass !❤
You are very welcome and it's a pleasure to help. Best of luck with your exam
@@imanmoaz cant believe you answered me !! Thank youu🤍🤍🤍🤍
Hey the most awesome man on CZcams :)
when you will complete this course? still need DFT,Sampling ,Modulation and many other topics :)
Hey, thank you for your comment. It made me very happy :) I will complete the course in the near future. My life has been hectic recently but I will get back to video making ASAP. Cheers!
really waiting :)
you made our life simpler ,giving so much knowledge in very short video and in a very simpler way :)
You are the teacher!
You are kind ;)
i have a question while proving the laplace transform of delta(t) why the integral of it is equal to 1
cant wait for the next tutorial ! please upload it soon
Sure thing. Sorry I have been super busy with some personal stuff recently but will upload the next video ASAP ;)
فوق العاده هست دمت گرم
Mamnonam Morteza jan, be man lotf dare ;)
sir u r completly awesome .....i have gone through your all videos related to signals and system...hatts off to u sir..
reality expo thanks a lot. please recommend this channel to your friends. cheers!
Hey Iman, you have a unique style in teaching.... Thank you for lecture.
Thank you very much for your kindness and all the positive feedback. I do appreciate it ;)
just excellent ,made my life easy .....
thank you! your lectures are awesome.
Thanks a bunch!
Excellent tutorials Iman. Extremely helpful! Is there an ETA for the Modulation/Demodulation and Sampling tutorials?
Thank you for imparting your knowledge onto us!
Thank you very much Abdulrahman. I'd love to upload the next tutorials ASAP but the last month was hectic as I moved to a new city and started a new job. I am still waiting for the furniture to set up my small studio and continue working on the channel. I am excited to get back on the track soon as my furniture will be delivered next week ;) Sorry for the delay and have a wonderful day.
Great explanation thank you
Daniel Rivera cheers!
Sir , which software you are using??
Owsome lectures
Castofly! It is available at www.castofly.com for Windows
Your explanation is awesome .. Many Thanks !
Thank you very much for your kind words!
@@imanmoaz Most Welcome, Are you going to cover digital filters topic ?
we need that you start from exp(jw0t) and to do the FT of this to obtain the dirac function ??? I can't do it
So FT separates a signal into frequencies, and IFT integrates the separate frequencies back into 1signal?
Yes, that's correct.
thank you so much
thank you for watching ;)
you are awesome...i have a question at 11:58...how you said that time period is infinity for a time period of (-1,1)?
Thank you very much Mazzullah. The signal is non-zero from -1 to 1 but the period is infinity. Basically, what I am trying to say is that any non-periodic signal can be considered periodic with the infinite period. Please let me know if it is not still clear.
thank you.i really appreciate your quick response.Still a little confused ..would you please elaborate how the time period is infinite ? can you give an example to show how we can considered a non periodic signal as periodic?
Hey again. Please consider the example that I covered at 7:41 in “Frequency domain - tutorial 2: Fourier series”. It is obvious that the period is 4. Now, visualize the case when the period is 40. So, it takes more time for the signal to repeat over and over. Now, visualize the case when the period is 40000. So, it takes a quite long time for the signal to repeat. When the signal is not periodic, we can just assume the period is infinity, i.e. the signal will repeat after infinite time! Does it make sense?
thank you :) crystal clear ..you are awesome
Mazzullah Khan cheers!
I.like it
Thanks for the awesome video! Is it possible to give out the notes of the lecture? Just like the faculty of khan does, and this will help to review what we have learn quickly.
Sure, I will release them soon. Honestly, I made my videos all ad-free to minimize distraction and hoped to get enough donation to get the channel going but unfortunately it didn't work. I want to stay away from ads as much as I can, but I might make my lecture notes plus extra examples available at a very very small cost (to make sure every single student on the planet can afford it).
fantastic！
why when you havn't do the TF of the cosin to show us how we can start with sin or cosin to showw us how we can obtain the delta function from Tf for this two function,iam blocked when I try
Sorry Sofi, I didn't understand your question. Could you please rephrase it? Thanks!
Rect = 5:12
7:26
33:42 Truth has been spoken!
hahaa, did you call yourself FT expert? ;)
You can do bitboxing with ur voice....
hahaa, honestly idk what that is! I googled bitbox but found different things! Is it a bad thing or good? :)))
@@imanmoaz bro search on CZcams you will find osm videos on bitboxing your voice is deep which is perfect for it...🙂
good morning sir thank you so much for your amazing tutorials you make it super easy but i want to ask about somthing our doctor gave as those two formulas for fourier transform X(ω)=∫[X(t)e^(-j2Πωt) ] dt
X(t)=∫[X(ω)e^(+j2Πωt)] dω so what is the deference betwen them and the ones you mentioned
sin(wt)u(t) proof please ㅜ.ㅠ
please watch my lecture on Fourier transform examples:
czcams.com/video/NGsAVTpUh_U/video.html
inelec kaml hna 😅
True😭
Lol!
The fuck why is there no examples of fourier transform pairs all over the internet only fucking proof and demostration
Please watch my video titled as "Fourier transform examples marathon". Hope it helps!