Thanks. I'm glad you liked it. Have you seen the other videos I've made in a similar style? "How to Understand Convolution" th-cam.com/video/x3Fdd6V_Hok/w-d-xo.html and "What is the Fourier Transform used for?" th-cam.com/video/VtbRelEnms8/w-d-xo.html
Excellent video! Nyquist sampling theorem says that if you want to figure out how fast the bike tire is moving (frequency) and which direction it's moving, you need to sample it at least twice as fast as it is spinning. Sample slower than that and it'll look like the wheel is spinning backwards, even when it's spinning forward. You won't be able to tell if the wheel is spinning forward at f_nyquist + delta or f_nyquist - delta. This is aliasing where the spectrum "folds back" onto itself about the Nyquist sampling rate. Some designs actually rely on sampling in higher Nyquist regions, though it requires a high pass filter or band pass filter to guarantee that there is no frequency content below that Nyquist region. Otherwise you will get an aliased spectrum.
Thanks. Yes, I've got a couple more videos explaining it in more detail: "Aliasing Ambiguity Explained" th-cam.com/video/zUAka4orrJA/w-d-xo.html and "What is Aliasing?" th-cam.com/video/B3nZUFNkTGY/w-d-xo.html
And this is why we need motion blur in videos; to reduce aliasing. Though to get rid of the aliasing all together we'd need at least a 720 degrees shutter which unfortunately is physically impossible, and it would also make everything looking a bit to smooth.
Thanks for your nice comment. I'm glad you like the intuition. I think it's so important to have different ways of thinking about mathematical equations and operations.
Thank you for this. I wish my professor had explained it this way. So much more intuitive than staring at sine waves of different frequencies trying to puzzle out what the heck aliasing is from that.
Thank you for making so many wonderful videos. An example I like to use involves an ordinary clock with hour and minute hands. If we look at the clock every 11 hours, then the hour hand will appear to move backward 1 hour. Similarly for the minute hand if we observe it too infrequently it too will appear to move strangely. And many other false or aliased outcomes occur by sampling too infrequently as you have so nicely demonstrated.
I really want to thank you, i have just understood decimation and interpolation with your videos , Good Luck from Algeria 🇩🇿 ❤️ I wish you make videos about Adaptive filters and Blind Source Separation , Thank you !
Hi, I really liked the environments that you recorded the videos in (next to the sea, etc); can you tell me what country/city is that? it was very beautiful
Glad you like the videos. Maybe I should do a video on the signals produced by disk brakes compared to rim brakes. Disks can certainly be more squeaky, but they definitely stop more quickly! ... my new bike has disk brakes 😁
Wonderful Explanation sir. But I want to ask a question: here while the camera captured the backward motion of the wheel its sampling rate was high? and if I want to get the correct movement of the wheel in the video should I have to keep my sampling rate low?
In some cases under-sampling can achieve the ultimate goal (eg. in some cases of digital down conversion), but in general you need to make sure you're sampling at least twice the rate of the change in the signal. You might like this video: "Which Way is the Propeller Spinning?" th-cam.com/video/niykPH0n4J0/w-d-xo.html
Hello professor, I really appreciate your special explanation. But, what I am still confused about is the phase reversal. With ALIASING, the wheel looks rotating backward because of its angular freq.. But, the textbook said it is because of the phase reversal and I cannot understand it. Could you please explain the relationship between backward spinning of the wheel and the phase reversal?
So with aliasing we should expect that higher frequency pitches would be of lesser quality than low pitch frequencies and middle pitch frequencies? But I feel like it's more complex than that because of some other videos I've seen.
@ I also edited my post…but you probably understood. But by lesser quality, I meant that higher frequencies pitches would be more likely to be distorted or vanish entirely?
It's important to understand that signals are not being "distorted" when they are sampled. And they are not "vanishing" either. All that is happening is that the continuous-time signal is being converted into a sequence of numbers (ie. the samples). If you try to reverse the process (digital-to-analog conversion) then you will be able to reconstruct the low frequency components of the original continuous-time signal exactly (ie. below the Nyquist frequency), but you won't be able to reconstruct the frequency components that were above the Nyquist frequency. The sampled energy from those frequency components will alias (or "fold back") into lower frequency components in the reconstructed signal. Hopefully this video will help: "Aliasing Ambiguity Explained" th-cam.com/video/zUAka4orrJA/w-d-xo.html
Sir why nobody teaches how things happen, how to figure things out as a curious yet not properly guided youngster like me???. And i really want to ask why on the world should we learn aliasing . Just because i took electronics in graduation ? How should i see the physics behind it to use it in daily life
Any continuous time signal (eg. voice signals, music, temperature changes, ...) and any analog image (video, photos, ...) that is stored on a computer or digital camera or memory stick or hard drive ... has been sampled. Basically sampling happens in anything in daily life that is controlled or measured by a digital system / computer.
Have to say that a new creative, successful explanation style is born. Thanks for creating the video. Cannot wait for more.
Thanks. I'm glad you liked it. Have you seen the other videos I've made in a similar style? "How to Understand Convolution" th-cam.com/video/x3Fdd6V_Hok/w-d-xo.html and "What is the Fourier Transform used for?" th-cam.com/video/VtbRelEnms8/w-d-xo.html
Excellent video!
Nyquist sampling theorem says that if you want to figure out how fast the bike tire is moving (frequency) and which direction it's moving, you need to sample it at least twice as fast as it is spinning. Sample slower than that and it'll look like the wheel is spinning backwards, even when it's spinning forward. You won't be able to tell if the wheel is spinning forward at f_nyquist + delta or f_nyquist - delta. This is aliasing where the spectrum "folds back" onto itself about the Nyquist sampling rate. Some designs actually rely on sampling in higher Nyquist regions, though it requires a high pass filter or band pass filter to guarantee that there is no frequency content below that Nyquist region. Otherwise you will get an aliased spectrum.
Thanks. Yes, I've got a couple more videos explaining it in more detail: "Aliasing Ambiguity Explained" th-cam.com/video/zUAka4orrJA/w-d-xo.html and "What is Aliasing?" th-cam.com/video/B3nZUFNkTGY/w-d-xo.html
And this is why we need motion blur in videos; to reduce aliasing. Though to get rid of the aliasing all together we'd need at least a 720 degrees shutter which unfortunately is physically impossible, and it would also make everything looking a bit to smooth.
Greatly appreciated professor, your initiative to give special importance to intuition when teaching a concept is what impresses me the most!
Thanks for your nice comment. I'm glad you like the intuition. I think it's so important to have different ways of thinking about mathematical equations and operations.
Thank you for this. I wish my professor had explained it this way. So much more intuitive than staring at sine waves of different frequencies trying to puzzle out what the heck aliasing is from that.
It's great to hear that my video helped you to visualise aliasing. I also wish my own professor had explained it this way - back when I was a student.
I don't think there is a better video than this to explain aliasing.... Thanks a lot for the effort n knowledge........
I'm so glad you liked the video. Thanks for your nice comment.
Very brilliant explanations! Haven't been to Manly since covid
Thanks. I'm glad you liked it. I'm guessing that the lack of hot days this year has also been a factor in Manly visits.
YOU ARE PERFECT! I AM WATCHING YOUR VIDEOS FOR 3 DAYS WOW
That's great to hear. I'm so glad you like the videos.
Thank you for making so many wonderful videos. An example I like to use involves an ordinary clock with hour and minute hands. If we look at the clock every 11 hours, then the hour hand will appear to move backward 1 hour. Similarly for the minute hand if we observe it too infrequently it too will appear to move strangely. And many other false or aliased outcomes occur by sampling too infrequently as you have so nicely demonstrated.
Thanks for sharing that example too!
A remarkable approach on the theory of aliasing ! Very well and comprehensive explained !
Thanks. I'm glad you liked it.
@@iain_explains I always do... ;-)
Thank you for this artfully made and thought-provoking film. Best Regards 😉
I'm so glad you liked it.
Really Thanks a lot Best explanation ever!!!
I'm so glad you liked it!
I really want to thank you, i have just understood decimation and interpolation with your videos , Good Luck from Algeria 🇩🇿 ❤️
I wish you make videos about Adaptive filters and Blind Source Separation , Thank you !
I'm glad the video was helpful. And thanks for the suggested topics. I've put them on my "to do" list.
Another great explanation. Thanks. The star jumps are a wonderful example.
Glad you liked it!
Hi, I really liked the environments that you recorded the videos in (next to the sea, etc); can you tell me what country/city is that? it was very beautiful
It's Sydney, Australia. I'm glad you liked the views. Perhaps I should try to include them in more of my videos ....
this channel is great!
thank you for all of your effort
Glad you like it! Thanks for your comment.
Professor, the most impressive is your didactic - the easy way you explain difficult terms. Thanks. Obs: rim brakes are better than disk brakes … 😂
Glad you like the videos. Maybe I should do a video on the signals produced by disk brakes compared to rim brakes. Disks can certainly be more squeaky, but they definitely stop more quickly! ... my new bike has disk brakes 😁
Wonderful Explanation sir. But I want to ask a question: here while the camera captured the backward motion of the wheel its sampling rate was high? and if I want to get the correct movement of the wheel in the video should I have to keep my sampling rate low?
In some cases under-sampling can achieve the ultimate goal (eg. in some cases of digital down conversion), but in general you need to make sure you're sampling at least twice the rate of the change in the signal. You might like this video: "Which Way is the Propeller Spinning?" th-cam.com/video/niykPH0n4J0/w-d-xo.html
Very clear and very good approach to move the concept to real world. Nice bicycle tough 👍🏻.
Glad you like it!
I like the bird yelling in the background towards the end
Amazing explanation!
Glad it was helpful!
The True Professor
Thanks for your nice comment. I'm glad you like the videos.
Wonderful explanation
Glad you liked it
you are a magician as i always said professor
I'm glad you're continuing to find the videos helpful.
That was so helpful, thank you so much!
Glad it was helpful!
thanks bro you are inspiring
I appreciate that!
Nice explanation sir
Thanks for liking
Hello professor, I really appreciate your special explanation. But, what I am still confused about is the phase reversal. With ALIASING, the wheel looks rotating backward because of its angular freq.. But, the textbook said it is because of the phase reversal and I cannot understand it. Could you please explain the relationship between backward spinning of the wheel and the phase reversal?
Hopefully this video will help: "What is Aliasing?" th-cam.com/video/B3nZUFNkTGY/w-d-xo.html
So with aliasing we should expect that higher frequency pitches would be of lesser quality than low pitch frequencies and middle pitch frequencies? But I feel like it's more complex than that because of some other videos I've seen.
I'm not sure what you mean by "lesser quality". Can you be more specific?
@ I also edited my post…but you probably understood. But by lesser quality, I meant that higher frequencies pitches would be more likely to be distorted or vanish entirely?
It's important to understand that signals are not being "distorted" when they are sampled. And they are not "vanishing" either. All that is happening is that the continuous-time signal is being converted into a sequence of numbers (ie. the samples). If you try to reverse the process (digital-to-analog conversion) then you will be able to reconstruct the low frequency components of the original continuous-time signal exactly (ie. below the Nyquist frequency), but you won't be able to reconstruct the frequency components that were above the Nyquist frequency. The sampled energy from those frequency components will alias (or "fold back") into lower frequency components in the reconstructed signal. Hopefully this video will help: "Aliasing Ambiguity Explained" th-cam.com/video/zUAka4orrJA/w-d-xo.html
Sir why nobody teaches how things happen, how to figure things out as a curious yet not properly guided youngster like me???. And i really want to ask why on the world should we learn aliasing . Just because i took electronics in graduation ? How should i see the physics behind it to use it in daily life
Any continuous time signal (eg. voice signals, music, temperature changes, ...) and any analog image (video, photos, ...) that is stored on a computer or digital camera or memory stick or hard drive ... has been sampled. Basically sampling happens in anything in daily life that is controlled or measured by a digital system / computer.
Was so easy to understand!
I'm glad to hear that.
But I have seen this backward motion of a car's wheel in real life so whats the reason behind that?
It's the same reason, except that in this case it's your brain that can't keep up with the rate of change of what your retinas are receiving.
Do you have a pet pterodactyl ?
🤣 ... Australian birds are very noisy!