Quite a few of you have commented that the diagram at 8:33 is incorrect, and that you can in fact reconstruct a perfect sine wave, not a "wonky" one like I've drawn. Turns out, they're right, but only when certain specific conditions are met. For a full discussion on this point, check out the following video: th-cam.com/video/Sb_4MS8l8yM/w-d-xo.html
Wow, it's a great honor to get a comment from you Destin. I've been following your work for a while now and you've been one of my inspirations :) Thank you very much for dropping by! Glad you like the intro! It's a mixture of mouth sounds and public domain audio.
NICE, good job. First time ever, someone explained it clearly and plain. Thank you so much!!! .....(10 min later) Wow, just clicked on your playlist - thank you, man, for bringing university into the living room - that's knowledge for everyone! I'm impressed :)
you explained in 10 mins where my Ph.D. lecture with 20 years couldn't... the best teacher is who explains the complicated topic in a simple manner where a common man can also understand.
Hello and thank you very much for your comment! Glad you found my work useful, though I'm sure in school, things need to be a lot more rigorous. Hopefully this is a good start for you to better understand what you're studying!
Thank you for this! I am studying this in my online university course, and couldn't wrap my head around it. Thank you for making this information so clear and easy to understand. You have a real skill for getting information across.
Jesus....You explained something my lecturer could not do for any entire semester. Thanks man. For some reason I used this stuff but never TRULY got the intuition. Thanks a lot.
Hello and thank you very much for your comment! Yeah I think tragically, schools tend to forget the "big picture" explainations that appeal to intuition, so students never really see how concepts link back to the real world. Glad to be able to fill that in for you!
who is this guy with so much precision? I love you man. sometimes I wonder why some of our university dons do not want to relax themselves and explain things this way? i sat for an hour lecture, but just couldnt figure out what my lecturer in school meant by this. Thanks a million
Hello and thank you very much for your comment! Very happy to be of help =) It's unfortunate that schools generally don't explain everything step-by-step and require some sort of self-research to really complete your understanding. But that's where I come in =)
I'm writing a report on Fourier Analysis (and writing code in MATLAB to show concrete examples) in which I'm expected to explain and describe Nyquist sampling frequency, as well as aliasing. This video just made my job a hell of a lot easier. Thanks dude!
+Orri Avraham You're welcome! That's what I like to hear - That people have found my work simple and easy to understand, because that's exactly what I aim for! Really happy to know I've achieved it. Thank you very much for your comment =)
Thanks. I am 60+ years and I learnt something today. The way you broke it down Now the reason why i watched this was to understand sampling when it comes to astronomical imaging. In Astronomical imaging, it's not how often you sample but the pixel size of the sensor in relation to the object you are imaging. for example to my understanding if you are imaging the planets then you pick a larger pixel size and if you do deep sky images ( of stars, galaxies, nebulae) you use smaller pixels.With the knowledge you have given which is very useful, I will try to now improve my understanding of this subject. Thanks again.
Hello and thank you very much for your comment! It was lovely to see you reason out the connection there to pixel size - Yes, in photography, we're doing *spatial* sampling as opposed to *temporal* sampling. Of course there are many other factors, such as the lens' ability to collect light, its aperture size and so on. But the basic intuition of course is - If something is significantly smaller than a pixel, all you're going to see is a speck of light, but no useful shape to work with.
So what I learned from this video is that human logic makes you can pay up to 80k a year to go to college and hear profs badly explain this concept, while this guy does it so well for free on TH-cam. What a beautiful society we live in.
Hello and thank you so much for your comment! Glad you found the video useful! If it's any consolation, college is a lot more than profs. It's the work they make you do, the connections you make and the experience you go through that'll count for something in the future!
Probably has something to do with the fact that no math is covered in this video. In class, you need to understand the frequency domain. This is the kind of video you'd want to watch before a lecture covers the topic.
Harry Nyquist (7 February, 1889-4 April, 1976) was an important contributor to communication theory, with work on the stability of feedback amplifiers, thermal noise, facsimile, television, telegraphy, and work on the Nyquist stability criterion. He left the world a better place. You are making the world a better place.
Hello and thank you very much for your comment! While the whole breaking the monitor thing might not quite work out, this comment means all the same to me! I'm very happy to have been of help!
Very well explained ,I have read this thing so many times in textbook but was never able to appreciate what is being told.but after listening to your lucid and beautifully designed video I have been able to get my head round it.thanks a ton from the bottom of my heart.you are brilliant
I am a civil engineering professor, your concept of Aliasing was clear without any ambiguity. I have listened to lectures of Professor's of IIT. You are excellent.
+S.I. CIMTHOG Hello and thank you for your comment! It's ok - The dislikes will definitely come, but what means a lot more to me are the constructive and nice comments, of which there are plenty =)
I don't know how old you were when you did this video, but you sure look very young and on top of that you sure know the subject. Great explanation by bringing it down to my level of understanding. Keep up the great work. Thank you.
hey dude. this video is amazing. you make it all seem so simple. do you have any sources. I'm trying to write a paper on sampling, I'd love to use the stuff you talked about but i need to be able to site it :(
Hello and thank you for your comment! Sorry I got around so late to your comment. I wasn't notified about it for some reason! Unfortunately no - I don't have any sources since what I'm covering here is quite superficial. However, if you look up Nyquist Theorem or Sampling on Wikipedia, you should find citations there that might be useful to you.
This was so much more helpful than my time spent studying this concept at SAE. I really appreciate the almost conversational and natural progression of your explanation. Rather than stopping the momentum of each point to recite and emphasize technical language, you convey the overarching process before tying everything to the (occasionally intimidating) terminology. This is an excellent way to communicate these concepts. Great job.
Thank you so much for this video. I learn better through someone speaking. So having you explain it, instead of me reading it, really helps! I'm learning sampling in an audio engineering course, and I couldn't quit grasp it on my own. One of my classmates linked this video in our community notes, so its thanks to them that I found this video!
Hello and thank you very much for your comment! Really glad to be of help :) And many thanks too to your classmate who shared my video! Appreciate their spreading the word.
Dude, as a physician I've tried to understad this concept several times before, in order to understand the workings of the pulsed wave doppler limitations for ultrasound. But since I've got no physics background, this has proved imposible. I mean, imposible up until now! Many many many thanks!
You did a really great job, I'd watch more of your videos just because how well you explain the topics with multiple examples. Thank you very much for this video.
This video helped me SO much in understanding this material. The words and definitions from my sonography book was confusing me, but your explanation and examples helped clarify material that I felt I would never truly get. THANK YOU! :)
In another video someone described how aliasing was a problem a problem in some older synthesizer especially when playing higher notes. I now understand this relationship.
You have a clear concept and I just can't explain you how much this video has helped me to clear my concept for my exam tommorow .. Thanks a lott for this video ,looking forward to more videos from you 😊😊👍🏻
@@NERDfirst yeah it went really well.. and a question regarding to same topic came in the exam, which i wrote elaborately explaining each point with daigram,the same way you did..!! Thanks to you ! 🙂🙂
Hello and thank you for your comment! I honestly didn't give it this much thought when drawing that, but luckily it works out - You can take the last "x" to be the beginning of the next oscillation which is not shown.
really wake me and wide up my eyes to hear this lecture. thanks. i need more video like this so it make me not bored to learn Digital Signal Processing Thanks a lot make interesting video.
You're welcome! It's unfortunate, but sometimes in university, professors have to cover a lot of the underlying theories and math, so that's why you feel they aren't as good. I don't blame them, but I'm glad I could help you fill in the gaps!
Good video, and your illustration at 8:36 points out how different the reconstruction is from the original when you get close to half the sampling frequency, at least when the reconstruction is to interpolate from point to point, rather than inverse Fourier transform. And to my knowledge DACs don't do inverse Fourier transform when they reconstruct. So this really calls for far higher sampling rates than twice the highest frequency you want to render.
Hello and thank you for your comment! Certainly, when basic linear interpolations are involved, a higher sampling rate could give you a better reproduction of the signal, even if aliasing does not take place.
Thanks a lot buddy... U made it easy to understand 😊 I had my exam today, nd saw ur video in the morning, nd luckily a question appeared from this topic, nd i could answer 😄😄 All thanks to u
Quite a few of you have commented that the diagram at 8:33 is incorrect, and that you can in fact reconstruct a perfect sine wave, not a "wonky" one like I've drawn. Turns out, they're right, but only when certain specific conditions are met. For a full discussion on this point, check out the following video: th-cam.com/video/Sb_4MS8l8yM/w-d-xo.html
You explained in 10min what my tutor couldn't in over an hour. Thanks mate,
Semester*
Same here :D
tuu bhi chat le uski...kitne rupay khae usse tune is comment ke liye??
ya bro it is true , he taught a lot in 10mins
this is a mood and its been three years since your comment ive been trying to understand this for a year
Your complete geekiness about this topic is a gift to us all
Thank you!
Hello and thank you very much for your comment! That's exactly what I hope to hear =) Glad to be of help!
Honestly you explained so much more straightforward than my college professors, glad I found your video
+pewpew king Thank you very much for your comment! Very happy to be of help :)
Awesome, thank you for this. Know that 5 years later, this is still helping people out
You're welcome! Definitely very happy to know that I've been able to help out so many people =)
Love your intro screen sounds.
Wow, it's a great honor to get a comment from you Destin. I've been following your work for a while now and you've been one of my inspirations :) Thank you very much for dropping by!
Glad you like the intro! It's a mixture of mouth sounds and public domain audio.
I love how you explain things from very simple concepts and then gradually go to more complex ideas. Thank you so much!
Hello and thank you very much for your comment! Very happy to be of help =)
NICE, good job. First time ever, someone explained it clearly and plain. Thank you so much!!! .....(10 min later) Wow, just clicked on your playlist - thank you, man, for bringing university into the living room - that's knowledge for everyone! I'm impressed :)
Hello and thank you very much for your comment! Really glad you've been finding my work useful!
you explained in 10 mins where my Ph.D. lecture with 20 years couldn't... the best teacher is who explains the complicated topic in a simple manner where a common man can also understand.
Hello and thank you very much for your comment! Glad you found my work useful, though I'm sure in school, things need to be a lot more rigorous. Hopefully this is a good start for you to better understand what you're studying!
It took my professor an hour to fail to explain these concepts! You're good, buddy. Real good! Thank you!
You're welcome! Very happy to be of help =)
Thank you for this! I am studying this in my online university course, and couldn't wrap my head around it. Thank you for making this information so clear and easy to understand. You have a real skill for getting information across.
Hello and thank you very much for your comment! Very happy to be of help =)
Jesus....You explained something my lecturer could not do for any entire semester. Thanks man. For some reason I used this stuff but never TRULY got the intuition. Thanks a lot.
Hello and thank you very much for your comment! Yeah I think tragically, schools tend to forget the "big picture" explainations that appeal to intuition, so students never really see how concepts link back to the real world. Glad to be able to fill that in for you!
Studying for my EIT five years after college, this video is pure gold for jogging my memory - thank you!!
You're welcome! Very happy to be of help =)
Damn yo, you're going to make a great professor one day. Thanks a lot for the video!
Hello and thank you very much for your comment! Very happy to be of help =)
who is this guy with so much precision? I love you man. sometimes I wonder why some of our university dons do not want to relax themselves and explain things this way? i sat for an hour lecture, but just couldnt figure out what my lecturer in school meant by this. Thanks a million
Hello and thank you very much for your comment! Very happy to be of help =) It's unfortunate that schools generally don't explain everything step-by-step and require some sort of self-research to really complete your understanding. But that's where I come in =)
I'm writing a report on Fourier Analysis (and writing code in MATLAB to show concrete examples) in which I'm expected to explain and describe Nyquist sampling frequency, as well as aliasing. This video just made my job a hell of a lot easier. Thanks dude!
+Dionysios Van Der Heynen Cheers! Happy to be of help. All the best for your work =)
very well done. Your explanation is more lucid and straightforward than most of the literature I've come by. Thank you!
+Orri Avraham You're welcome! That's what I like to hear - That people have found my work simple and easy to understand, because that's exactly what I aim for! Really happy to know I've achieved it. Thank you very much for your comment =)
I never leave comments on TH-cam but this was too helpful not to. Thank you
You're welcome! Very happy to be of help =)
same lol
Thanks. I am 60+ years and I learnt something today. The way you broke it down Now the reason why i watched this was to understand sampling when it comes to astronomical imaging. In Astronomical imaging, it's not how often you sample but the pixel size of the sensor in relation to the object you are imaging. for example to my understanding if you are imaging the planets then you pick a larger pixel size and if you do deep sky images ( of stars, galaxies, nebulae) you use smaller pixels.With the knowledge you have given which is very useful, I will try to now improve my understanding of this subject. Thanks again.
Hello and thank you very much for your comment! It was lovely to see you reason out the connection there to pixel size - Yes, in photography, we're doing *spatial* sampling as opposed to *temporal* sampling. Of course there are many other factors, such as the lens' ability to collect light, its aperture size and so on. But the basic intuition of course is - If something is significantly smaller than a pixel, all you're going to see is a speck of light, but no useful shape to work with.
I pretty much knew the information presented, but I could never...NEVER explain it so eloquently. Nicely done 👌
Hello and thank you very much for your comment! Glad you liked the video =)
So what I learned from this video is that human logic makes you can pay up to 80k a year to go to college and hear profs badly explain this concept, while this guy does it so well for free on TH-cam. What a beautiful society we live in.
Hello and thank you so much for your comment! Glad you found the video useful!
If it's any consolation, college is a lot more than profs. It's the work they make you do, the connections you make and the experience you go through that'll count for something in the future!
Probably has something to do with the fact that no math is covered in this video. In class, you need to understand the frequency domain. This is the kind of video you'd want to watch before a lecture covers the topic.
Harry Nyquist (7 February, 1889-4 April, 1976) was an important contributor to communication theory, with work on the stability of feedback amplifiers, thermal noise, facsimile, television, telegraphy, and work on the Nyquist stability criterion. He left the world a better place. You are making the world a better place.
Hello and thank you very much for your comment! That's high praise! Glad you liked the video =)
I want to break through my monitor and hug you, you're saving me dude!
Hello and thank you very much for your comment! While the whole breaking the monitor thing might not quite work out, this comment means all the same to me! I'm very happy to have been of help!
Very well explained ,I have read this thing so many times in textbook but was never able to appreciate what is being told.but after listening to your lucid and beautifully designed video I have been able to get my head round it.thanks a ton from the bottom of my heart.you are brilliant
Hello and thank you very much for your comment! Glad to be of help =)
Can you teach MRI physics?it is very tough
@@shashwatpriyadarshi972 Hello and thank you for your comment! I'm afraid not, my background is computer science.
No problem sir
Best intro video on sampling on the internet. Thank you so much!! This helped a lot.
+floatingroses You're welcome! Very happy to be of help =)
I am a civil engineering professor, your concept of Aliasing was clear without any ambiguity. I have listened to lectures of Professor's of IIT. You are excellent.
Hello and thank you for your comment! Glad you liked the video =)
You did an amazing job in explaining this topic. Who is watchin in 2019
Hello and thank you very much for your comment! Happy to be of help =)
You explained brilliantly in a simple way what most literature makes complex. Nice work. Well done man.
Hello and thank you very much for your comment! Very happy to be of help =)
Your way of teaching is awesome.
Thank you very much! Very happy to be of help =)
Due to the pandemic, all of my classes are online, and basically, teach yourself. Your video was truly helpful.
Hello and thank you very much for your comment! Glad you liked the video =)
very clear and concise presentation of the idea
Explaining 3 important concepts in such a short time just shows the clarity of your concepts. Thanks for your knowledge🙂
Hello and thank you very much for your comment! Glad you found the video useful =)
@@NERDfirst I am also glad to found the video
I still do not know why some guys who do not know Jack dislike this great video
+S.I. CIMTHOG Hello and thank you for your comment! It's ok - The dislikes will definitely come, but what means a lot more to me are the constructive and nice comments, of which there are plenty =)
After seeing your lecture, now I can feel what does it mean by sampling & aliasing. Really great explanation.
Hello and thank you very much for your comment! Very happy to be of help =)
I'm so grateful, that I've found this video. Super helpful, and easy to grasp!
Hello and thank you very much for your comment! Glad to be of help =)
Your explanation is crystal-clear. Iam completely know nothing about this topic/field. But your explanation is very understandable by general people
Hello and thank you for your comment! Very happy to be of help =)
Mate you have SAVED MY LIFE. THANK YOU, AND PLEASE KEEP MAKING THESEEE🙌🏻
Hello and thank you very much for your comment! Very happy to be of help =)
This is the best explanation I can find on this topic. It’s a confusing subject but you made it so clear. Thank you so much !!
You're welcome! Very happy to be of help =)
Such a precise explanation...I am impressed with the content and the amount of hardwork you have put in editing the video
Hello and thank you very much for your comment! Really glad you liked the video =)
This is the best video I've ever watched about Signal Processing... Thank you so much!
You're welcome! Very happy to be of help =)
this is seriously the best video on this subject. thank you very much.
+Jose Daniel Hello and thank you very much for your comment! Glad to be of help =)
I don't know how old you were when you did this video, but you sure look very young and on top of that you sure know the subject. Great explanation by bringing it down to my level of understanding. Keep up the great work. Thank you.
Hello and thank you very much for your comment! 2015... I was 24 back then! Time flies =)
Either way, very happy to be of help =)
Thanks for this video, just helped my girlfriend with her Embedded Systems exam :)
+Kevin Norman That's great! Here's wishing her the best of luck for her exam =)
hey dude. this video is amazing. you make it all seem so simple. do you have any sources. I'm trying to write a paper on sampling, I'd love to use the stuff you talked about but i need to be able to site it :(
Hello and thank you for your comment! Sorry I got around so late to your comment. I wasn't notified about it for some reason!
Unfortunately no - I don't have any sources since what I'm covering here is quite superficial. However, if you look up Nyquist Theorem or Sampling on Wikipedia, you should find citations there that might be useful to you.
I'm sure you helped sample her embedded system, if you know what I mean.
This was so much more helpful than my time spent studying this concept at SAE. I really appreciate the almost conversational and natural progression of your explanation. Rather than stopping the momentum of each point to recite and emphasize technical language, you convey the overarching process before tying everything to the (occasionally intimidating) terminology. This is an excellent way to communicate these concepts. Great job.
Hello and thank you very much for your comment! Very happy to be of help, and glad you found it useful! =)
You just got a new Subscriber. Thanks for such an amazing explanation.
+Oliver Joshua Jacob Hello and thank you for your comment and support! Very happy to be of help =)
Thank you so much for this video. I learn better through someone speaking. So having you explain it, instead of me reading it, really helps! I'm learning sampling in an audio engineering course, and I couldn't quit grasp it on my own. One of my classmates linked this video in our community notes, so its thanks to them that I found this video!
Hello and thank you very much for your comment! Really glad to be of help :) And many thanks too to your classmate who shared my video! Appreciate their spreading the word.
Thank you man!!! You helped me a lot!!!
You're welcome! Very happy to be of help =)
Dude, as a physician I've tried to understad this concept several times before, in order to understand the workings of the pulsed wave doppler limitations for ultrasound. But since I've got no physics background, this has proved imposible. I mean, imposible up until now! Many many many thanks!
Hello and thank you very much for your comment! Very happy to be of help =)
Thank you so much for this! It was really useful :)
You're welcome! Very happy to be of help =)
I knew there was something I wasn't getting about music production and this was it! Invaluable, thank you so much.
You're welcome! Very happy to be of help =)
Cheers buddy very useful
+D Hobbs Thank you! Glad to be of help =)
I had a 3 hrs class today. This video went better than the entire class.
^_^ Thanks
You're welcome! Glad to be of help =)
i respect you.
+donghee lee Thank you very much =)
After watching many videos, this is the best explanation I've watched
Hello and thank you very much for your comment! Glad you liked the video =)
Was very informative and lucidly explained. A great teacher always tries to teach the slowest student. Amazingly done.
Jivitesh, India
Hello and thank you very much for your comment! That is wonderful to hear, Glad you liked the video =)
You are a legend mate . The simplicity with which you explained 🙌, helped me a lot to prepare for my interview.
Hello and thank you very much for your comment! Very happy to be of help and all the best for your interview!
Very helpful video!! You explained everything I needed to understand in 10 minutes which my professor failed to make me understand in 2 hours......
Hello and thank you very much for your comment! Very happy to be of help =)
I have an exam today, and this was the only topic that was bugging me. Thanks man, now I guess I am ready to score full marks!!
Hello and thank you for your comment! Hope you did well =)
I've been confused about this subject since it was introduced last semester. So clear and concise! Thanks so much for making this video!
Hello and thank you very much for your comment! Glad to be of help =)
You explained this 10x better than my professor. Thank you so much!
You're welcome! Very happy to be of help =)
You are the best! My teacher couldn't explain this as you did in this video! Thank you so much!
You're welcome! Very happy to be of help =)
i just love the way you explained all this in just 10 minutes! thank you so much!
You're welcome! Glad you found the video useful! Seems I achieved what I set out to do then :)
Congratulations! A very nice explanation that I couldn't have in my undergrad classes.
Hello and thank you very much for your comment! Glad you found the video useful :)
You explain better than my professor, thanks dude. You just earned my subscription :)
You're welcome! And thank you very much for your comment and support =)
You did a really great job, I'd watch more of your videos just because how well you explain the topics with multiple examples. Thank you very much for this video.
Hello and thank you very much for your comment! Glad to be of help =)
This video is such a good watch to get that intuition of the Nyquist Shannon Theorem. Thank you!
You're welcome! Very happy to be of help =)
This video helped me SO much in understanding this material. The words and definitions from my sonography book was confusing me, but your explanation and examples helped clarify material that I felt I would never truly get. THANK YOU! :)
You're welcome! Very happy to be of help =)
You made my night, bro! You are superhuman. Keep sharing the light and peace to you!
Hello and thank you very much for your comment! Very happy to be of help =)
OMG...EXACTLY 2 years ago you made the video....GENIUS!
I'm surprised it's only two years old! Felt like much longer. Very happy to be of help =)
Wonderfully explained! I'm currently trying to self-learn signal processing with little foundational knowledge and this video was of great help!
Hello and thank you very much for your comment! Glad to be of help :)
this is fantastic, you explained to me in 10 minutes what other videos, and my professor couldnt in 3 weeks - month. thank you
You're welcome! Very happy to be of help =)
needed this for it's about time for science olympiad! you are literally a godsend
Hello and thank you for your comment! Very happy to be of help =)
In another video someone described how aliasing was a problem a problem in some older synthesizer especially when playing higher notes. I now understand this relationship.
Hello and thank you for your comment! That's a good example of aliasing in action!
you broke it down to simplest terms. best way of explaining !
Hello and thank you very much for your comment! Very happy to be of help =)
Thank you for this great video, it is ideal for people who didn’t take Physics in higher grades, but are now studying Computer Science
Hello and thank you for your comment! Glad to hear, happy to have been of help =)
@@NERDfirst Greetings from Germany by the way!)
Tomorrow is my exam watching this video now. what a clear explanation. Thank you.
Hello and thank you for your comment! All the best for your exam!
Loved your way of teaching, you make it so simple in explaining that any beginner can understand... Like me:)
Hello and thank you very much for your comment! Glad you liked the video =)
You have a clear concept and I just can't explain you how much this video has helped me to clear my concept for my exam tommorow .. Thanks a lott for this video ,looking forward to more videos from you 😊😊👍🏻
Hello and thank you very much for your comment! Hope the test went well =)
@@NERDfirst yeah it went really well.. and a question regarding to same topic came in the exam, which i wrote elaborately explaining each point with daigram,the same way you did..!! Thanks to you ! 🙂🙂
Singapore needs more people like you. Keep going,
Hello and thank you for your comment! Glad you liked my work =)
Thank you so much for this. Never thought I’d say this about something related to signals and systems, but this is simple and clear!
You're welcome! Very happy to be of help =)
Was looking for a video to refresh the basic principles of PCM, kudos
Cheers! Glad to be of help =)
I haven't found such a great explanation in anywhere. Thank you so much. It was very clear. I am happy that I learned new things :)))
You're welcome! Very happy to be of help =)
At 8:21 the signal is sampled at exactly 2b and i see 13 red xs. The frequency of the signal is 6. So wouldn't exactly 2b = 12 not 13?
Hello and thank you for your comment! I honestly didn't give it this much thought when drawing that, but luckily it works out - You can take the last "x" to be the beginning of the next oscillation which is not shown.
Saved me an hour before my exam! Thanks man.
You're welcome! Hope the exam went well :)
Hey, thanks a lot🤩 You have explained in really great manner which keeps listener engaged and also creates more interest.
Hello and thank you very much for your comment! Very happy to be of help =)
When I read it from the book, I was like reading Sanskrit 😅 but your explanation made it all clear ! You should be a teacher ! Thank you 🙏
Hello and thank you very much for your comment! I actually _am_ a teacher! Anyway, very happy to be of help =)
really wake me and wide up my eyes to hear this lecture. thanks. i need more video like this so it make me not bored to learn Digital Signal Processing
Thanks a lot make interesting video.
You're welcome! Very happy to be of help =)
Amazing stuff mate. I’m a radiology resident. Helped me a lot.
Hello and thank you very much for your comment! Glad to be of help =)
Thank you for this video - I now understand something that fully flew over my head the first time round.
You're welcome! Very happy to be of help =)
2023 and still find this explanation is really good !
Hello and thank you very much for your comment! Glad you liked the video =)
Excellent explanation and pace of video. Easy to understand even for someone like me new to this topic.
Hello and thank you for your comment! Glad to be of help =)
Omg you are waaaay better than those professors in my Uni. Thanks a lot!
You're welcome! It's unfortunate, but sometimes in university, professors have to cover a lot of the underlying theories and math, so that's why you feel they aren't as good. I don't blame them, but I'm glad I could help you fill in the gaps!
Good video, and your illustration at 8:36 points out how different the reconstruction is from the original when you get close to half the sampling frequency, at least when the reconstruction is to interpolate from point to point, rather than inverse Fourier transform. And to my knowledge DACs don't do inverse Fourier transform when they reconstruct. So this really calls for far higher sampling rates than twice the highest frequency you want to render.
Hello and thank you for your comment! Certainly, when basic linear interpolations are involved, a higher sampling rate could give you a better reproduction of the signal, even if aliasing does not take place.
By far the best explanation I have seen on the subject, thanks so much!
+SM2GXN You're welcome! Happy to be of help =)
Your videos are really enlightening, in the perspective of a high school student!
That's great to hear! I'm glad you're enjoying my work :)
Excellent explanation. A very grateful student here.
Hello and thank you very much for your comment! Glad to be of help =)
Just before my exams this video helped a lot. Thanks.
You're welcome! All the best for your exam =)
Thanks a lot buddy...
U made it easy to understand 😊
I had my exam today, nd saw ur video in the morning, nd luckily a question appeared from this topic, nd i could answer 😄😄
All thanks to u
You're welcome! That's great to hear! Hope you do very well on your exam =)
Thank you for the video it really helped me with my college work and you explained it very clearly and was detailed enough thank you
you explained better than my professor in electrical measuring system.
Hello and thank you very much for your comment! Glad to be of help =)