I only discovered these videos yesterday and I am simply blown away. Thanks a lot for putting in all this enormous effort to make them, Akash. These are extremely well done and the subjects are excellently explained. Fantastic work! 🙏
Dear Akash, I'm just an audiophile who loves music and keen to learn about it. Your videos are making me even more curious. You are an amazing teacher. 🙏. You have inspired me. Thank you
Man, you are more knowledgeable than the best professors in the world. Your way of explanation is phenomenal. Keep patience mate, you will reach more than a million subs in the next couple of years. Keep making these videos, you are serving humanity in a very very positive way. Thanks a lot
Thanks a lot for the compliments man! Although, I don't pretend to know it all. All of these videos were researched thoroughly, and I learnt quite a lot while doing that. And yet, there are a few mistakes here and there, that I discovered later. It's a learning process for me, as it is for you! But I really appreciate the positive feedback, and yea, I'll continue to do more.
Wow! I am stunned by the quality of your videos, they are just perfect. I'm new to the topic and this is hands down the best video I've yet seen on it.
I second this. Excellent videos! Using these to help my students better visualize the process in my computer science class now. Thanks, Akash! Very well done.
@@akashmurthy Don’t sweat it. It is impossible to make a video without small mistakes and it does not detract from your great information. Watching your dither videos now.
The process of recording sound stored in the form of thousands of indivdual measurement each at a discrete unit of time called.. very thanks for a super video....
Beating is what is used for tuning pipe organs. The pipes called principals have the least amount of tuning degradation over time, so to tune the other voices, you pull the principal plus the desired voice, then listen to the beating; tuning the desired voice is then done by miniscule adjustments of that voice until the beating stops.
Hey Akash! I recently found your videos and they are a blessing. I'm an Audio Engineer and Comm. Studies (with emphasis in Film & Media) major, that has been working in professional A/V for the last 5 years now. This series is helping me study for CTS, and just overall knowledge refresher. Thank you!
Thank you from the bottom of my heart,now I understand the sampling theory. I’ve been attending the lectures and the doctor keeps talking about it and never understand what he says 😅
All good, apart from two things. 1. Is really difficult to band limit a signal with such a steep filter. I am talking abut recording real audio signal , not a generated one, and encoding to CD digital format. 2. The theorem works, and is true to identify only sinusoidal signal long enough in time, and constant in frequency and amplitude. In case we approaching the upper limit of the band , and the pulse is short we may not have enough iterations to correctly identify a signal. Example is; the occurrence of one single wave in 19KHz band recorded with a CD standard 44.1KS/s. The real audio consists at most of fading impulses, rather than long in time and continuous in amplitude sinewaves, that is why I consider the CD format to be lossy and a higher sample rate well be beneficial, 48 or 96KS/s. The reconstruction of impulses by DACs is often an approximation.
first i was about to draw some panels to illustrate the Sample-Rates and what it means to higher frequencies. Then i thought, i should first look if someone already did it so that i could simply share a link. THEN i found THIS one and learned more details on something i though i already knew :D - Thank you!
many thanks for the video. When you said that it was a mathematically unique solution combined with the graphic it clicked in my head because I realized even before you said it that only one wave form at a certain frequency form could pass through all of the points at that same time. Really interesting !
A great video and explanation. But I'm confusing some points that you explained. @17:07 about the extra high-frequency content. Why it has an extra high-frequency content even if the generator produced the pure single signal at 3.9kHz?
This is super high quality precious content ... made with effort and commitment. No only his theoretical concepts are clear but also way of transforming them and explaining them is very good Much appreciated
I always sample at speeds well above that established by the theorem, since that way I can dispense with the design of very high-order filters that resemble ideal filters as much as possible, and use low-order filters... although of course this implies that electronic devices must also be able to handle such high frequencies. A very educational video
Wow, I came to your site to learn PCM which you will cover in part 9 or 10 and here as a bonus you have covered the free DAW software Audacity which as a beginner hobbyist, I actually want to learn to use with my music keyboard and computer. You showed us amazing things Audacity can do much better than sites dedicated to Audacity have shown me. Its like an Oscope and a spectrum analyzer. I want to watch all of your videos.
came here from signals-systems & DSP courses, because of stucking in sampling and continuous-discrete conversion. I have to say that, this video is quite good at explaining the subject intuitively and visually. It can be said that you are showing both whole and the pieces of the topic, this is a good approach to explain it. Sampling-Discretization-Periodization-Modulation, these topics needs to be explained well. I have still problems on understanding the CT to DT conversion, how this conversion occurs mathematically ? I mean, how to transform continuous time x(t) to sequence x[n] , mathematically? what is the operator that converts ""impulse(t) >> to impulse[n] with amplitude of 1"" or ""x(t) . p(t) impulse train >> to x[n] as a sequence"" x(t) . p(t) could be represented as = summation the series of x(nT) . impulse ( t - nT ) But this is still not equal to a sequence of x[n] , because it contains scaled impulses with amplitude of infinity, right? Therefore I am trying to understand what actually this conversion and this impulse are. What is the title of topic/video that covers this point? Thank you for helping.
Sampling theorem uses the keyword 'atleast' and we know that we cannot recover signal if we sample exactly at the Nyquist rate as discussed at 8:51. So shouldn't the theorem state that a band limited continuous time signal can be accurately converted to and from digital signal when sampled at a rate, 'more' than twice as high as the highest frequency component of the waveform? I have just replaced 'atleast' with 'more'
Thank you for the clarification. Many don't realise this fact and use the expression fs>=2fmax conveniently. I would also like to thank you for the simplicity and quality of this educational video. Looking forward for more.
Hey, you make learning so easy for me by making these videos. They are well produced, the tempo is perfect, all the necessary information is included and your lecturing style makes it seem like you go through the thinking process alongside us which really makes understanding all this completely effortless. Great great work!
Thank you very much! I'm glad to hear you like the style of the videos. It was an intentional choice to go through all the common questions that I had when learning these concepts and answering them.
I love the way you explain it 💖 The way you work on each topic which seems complex You are incredible The graphics and voice are really making it a pleasant learning of joy Please dont stop 👍 I love the way you put real life into dumb equations .
Very nice video! Thank you very much. Questions to you - why do we need band limiting when the original signal in Audacity is to be created for 3.999KHz ? Where will the high frequencies come from which are to be band limited? And if there are higher frequencies, wouldn't we need to sample w.r.t that value (Fmax will change)? Thanks again.
Hello, I didn't quite understand the part of leaving a buffer between required frequency and nyquist frequency: I understand that when converting digital signal back to analog signal, the low pass filter does not perfectly remove all undesired high frequency component, so we have a small portion of signal goes beyond the desired frequency. Whether setting the a buffer or not, this small portion of high frequency signal will always exist (Like for the buffer case you show at 18:56, there is a chunk in the buffer area). I can see that this region is distanced from the nyquist frequency. I don't understand why is it better, because in both scenario (desired signal frequency near 1/2 of sample rate or much lower than sample rate), we both have an undesired chunk.
@@mingzhou2213 Aliasing. I go into more detail on Aliasing in the next videos in the series. But you want to eliminate any frequencies beyong the nyquist, otherwise you run the risk of the the frequencies aliasing and being bounced back into the audible range of the signal. This happens because of the mathematical constraints of discrete signals in a digital system.
Very cool stuff man! loving your tutorials.. Am very glad you have embarked upon this journey.... There's always something new to learn! good stuff.. keep it up! :) cheers
Thanks man! The plan is to continue deep diving into audio concepts and getting as low level as possible while still being engaging and accessible enough. Thanks for the support, and for checking it out!
Thank you so much for this tutorial man, I have a kinda stupid question, if the sine wave is a single frequency with no harmonics and is already band limited , why did the 3999 frequency cause aliasing when the sample rate was 8000 Hz when we dont even need a band limiter for this sine wave, is it because it was digital to analog?, because it was produced digitally so it would have an intermediate stage with high frequncies? , and if it was analog to digital would it still cause aliasing ? Again, sorry if its a stupid question but its been bugging me
At 2Hz, there's no guarantee that a 1Hz signal will be sampled correctly. If the phase is a particular value, then the signal's sampled points all lie on the zero value position, treating the signal as silenced out.
Excellent lesson, sometimes a little lost coz my english but mostly the visual helps. Just one point to explain, your experience at 8:21. a tone at 4kHz and a sample rate at 8KHz showing no waveform and producing no sound. Is it same event when the frequencies = sample rate ? ( for the same example , if we have a tone at 4Khz with a sample rate at 4Khz)
Thank you! So, trying to represent any frequency above the Nyquist will cause the signal to alias. You can check out video #4 Aliasing. But in essense, if you generate a 4kHz signal at a sample rate of 4kHz, the signal will be interpreted as 0Hz. So yes. It will be a very similar result as that of the Nyquist frequency(2kHz).
@@akashmurthy Yes I watched all now. Lot of infos in my brain, but the biggest discovery was about the fact that the sound is reproduced thanks to math and not directly by sample rate, as long as we respect the theorem. I have two questions if you have time. 1) There is a big discussion in a forum about converting samples. For example with kontakt libraries. They are taking a lot of space (by hundred of GB) , some people convert them to 16Bits and others thinking of even converting to 44.1Khz. I understand that the choice of sample rate and bit depth is more for the recording, but what about sample already digital ? My opinon would be to choose 44.1Khz (coz it's enough) and 24 bits just to avoid plugins "destructing the quality" ( I have read that plugins do that so better to have lot of bits ) and for the dynamic range which looks important. against clipping. 2) One of the explanation of Hi-res is that when you cut at 44.1KHz, you will lose harmonics , timbre and color of the sound. does it make sense ? thank you and sorry for the long msg
@@josuefox hey, thanks for the questions. Choosing bit depth is only a consideration when converting from analog to digital or from digital to analog. Changing the bit depth after a signal has already been sampled does not make a lot of sense. In DAWs, the sample values are represented as floating point values. Plugins use floating point calculations in 32 bit or 64 bits of precision. They rarely ever operate in 16/24 bit fixed point. And no, down sampling to a rate of 44.1kHz from something higher does not lead to loss of audible harmonics. But it does depend on the quality of the anti Aliasing filter that's doing the conversion.
![ARGENTINA vs. CHILE [3-0] | RESUMEN | ELIMINATORIAS SUDAMERICANAS | FECHA 7](http://i.ytimg.com/vi/De3AWmXzhuA/mqdefault.jpg)
I only discovered these videos yesterday and I am simply blown away. Thanks a lot for putting in all this enormous effort to make them, Akash. These are extremely well done and the subjects are excellently explained. Fantastic work! 🙏
Thank you so much! I'm glad you found the channel.
I also have had my mind blown after discovering these videos "yesterday" (1 year after your comment 😅)
this might be the best video explaining those digital signal processing concepts
Dear Akash, I'm just an audiophile who loves music and keen to learn about it. Your videos are making me even more curious. You are an amazing teacher. 🙏. You have inspired me. Thank you
Thank you very much for the kind comment!
Man, you are more knowledgeable than the best professors in the world. Your way of explanation is phenomenal. Keep patience mate, you will reach more than a million subs in the next couple of years. Keep making these videos, you are serving humanity in a very very positive way. Thanks a lot
Thanks a lot for the compliments man! Although, I don't pretend to know it all. All of these videos were researched thoroughly, and I learnt quite a lot while doing that. And yet, there are a few mistakes here and there, that I discovered later.
It's a learning process for me, as it is for you! But I really appreciate the positive feedback, and yea, I'll continue to do more.
You are saving my university year!
Haha..good luck with college!
Saving mine too 🤣
Wow! I am stunned by the quality of your videos, they are just perfect. I'm new to the topic and this is hands down the best video I've yet seen on it.
Thanks a lot of checking it out!
I cannot express how much I love this video
Aww, thanks very much!
This shows the depth of your understanding and your willingness to share the knowledge with others. Excellent work 👏👏
Thank you so much for your feedback!
You are doing an amazing job man !! This playlist is so helpful 👀👀
Thanks very much!
Akash isn't a good explainer. He is a GREAT explainer. I am very impressed!!😊
Thank you kind sir!
These videos are pure Gold Akash! Really well produced and well chalked out. Massive props 🙏🏼
Thanks a lot! :)
I second this. Excellent videos! Using these to help my students better visualize the process in my computer science class now. Thanks, Akash! Very well done.
Thank you Jason! I'm glad you're able to use these in an academic setting!
Small mistake at @4.20 as it is 1/s not 1/s^-1. But this is one of the best videos on this topic.
Great spot! Thanks..I cringe at this mistake whenever I watch it back.
@@akashmurthy Don’t sweat it. It is impossible to make a video without small mistakes and it does not detract from your great information. Watching your dither videos now.
The process of recording sound stored in the form of thousands of indivdual measurement each at a discrete unit of time called.. very thanks for a super video....
That's the best representation of sampling!
Beating is what is used for tuning pipe organs. The pipes called principals have the least amount of tuning degradation over time, so to tune the other voices, you pull the principal plus the desired voice, then listen to the beating; tuning the desired voice is then done by miniscule adjustments of that voice until the beating stops.
This is where the maths and physics are NOT boring. Your explanation is genius Akash. Thank you
Thanks so much mate!
best video ever for audio processing
A god amongst men. Thank you for representing concepts in easy to digest youtube videos! Reading university books is so draining by comparison lol
T'is but a man, but a man with time. Thanks mate, glad you found it useful!
Since my knowing of this theorem, I have always tried to understand this.This video really makes me to understand.Thanks.
Glad it helped you out!
Hey Akash! I recently found your videos and they are a blessing. I'm an Audio Engineer and Comm. Studies (with emphasis in Film & Media) major, that has been working in professional A/V for the last 5 years now. This series is helping me study for CTS, and just overall knowledge refresher. Thank you!
That's awesome to hear, thanks for sharing!
Thank you from the bottom of my heart,now I understand the sampling theory.
I’ve been attending the lectures and the doctor keeps talking about it and never understand what he says 😅
Haha, that's awesome! It's quite simple, once you get a hang of it..
probably the most underrated series of videos on youtube
Love this! And the nod to Monty 😊👌
I was going to write the exact same thing lol
All good, apart from two things.
1. Is really difficult to band limit a signal with such a steep filter. I am talking abut recording real audio signal , not a generated one, and encoding to CD digital format.
2. The theorem works, and is true to identify only sinusoidal signal long enough in time, and constant in frequency and amplitude. In case we approaching the upper limit of the band , and the pulse is short we may not have enough iterations to correctly identify a signal. Example is; the occurrence of one single wave in 19KHz band recorded with a CD standard 44.1KS/s. The real audio consists at most of fading impulses, rather than long in time and continuous in amplitude sinewaves, that is why I consider the CD format to be lossy and a higher sample rate well be beneficial, 48 or 96KS/s. The reconstruction of impulses by DACs is often an approximation.
This series of videos are simoly amazing! Thank you so much for explaining audio processing that way :)
Thank you! I'm glad you found these useful!
6:22 I realized few seconds later its you voice! Graphics : 100/100
Yea! It was quite easy to do, but thanks for noticing!
Amazing. Absolutely amazing animation and explanation on this concept.
Thank you for the fantastic work!
Thank you so much for the support! :)
first i was about to draw some panels to illustrate the Sample-Rates and what it means to higher frequencies. Then i thought, i should first look if someone already did it so that i could simply share a link. THEN i found THIS one and learned more details on something i though i already knew :D - Thank you!
Glad you found it helpful, thanks!
Congratulations Akash...The kind of quality it contains surprised me....Initially, I thought it was done by some American guy...
This video is something else... The quality of explanation and animation are so good. Now I can do seminar about this topic without hesitation.
Akash, you are in my brain right now!
Sorry to intrude 😅
many thanks for the video. When you said that it was a mathematically unique solution combined with the graphic it clicked in my head because I realized even before you said it that only one wave form at a certain frequency form could pass through all of the points at that same time. Really interesting !
Great! I'm glad the graphics were useful.
Excellent video and presentation.. I can already imagine this channel with 10K subs in few months from now. Good luck.
Cheers! Thanks for taking the time out to write that!
my God! your work is simply amazing. thank you so much!!!
Thanks so much man! :)
its just so nice to find good content in non common topics. thks it helped me.
Glad it helped mate!
A great video and explanation. But I'm confusing some points that you explained. @17:07 about the extra high-frequency content. Why it has an extra high-frequency content even if the generator produced the pure single signal at 3.9kHz?
Man , that visualisation of aliasing is awesome!!
Cheers man! There another video in the series, number 4, that talks about aliasing with a bunch more visualizations. Thought that might interest you!
The graphs and animations complement your explanation really well!
Thanks very much!
Awesome, Akash! You speak so clearly and interestingly.
these videos are very well explained and put together. thank you!
Thanks very much!
I love this video a lot. Thank you. God bless you
You're welcome! :)
This Channel is amazing, and is filling in a lot of holes made by my DSP professor. Great stuff
That's high praise! Thanks very much :)
RESPECT for the top quality videos 🧠 way better than most uni lectures
Cheers mate!
Bro you are just awesome. Your animation and the fluency of describing is mind blowing. Love to watch your videos. Keep it up brother.
Thanks very much mate!
This is super high quality precious content ... made with effort and commitment.
No only his theoretical concepts are clear but also way of transforming them and explaining them is very good
Much appreciated
Thanks very much mate! :)
I always sample at speeds well above that established by the theorem, since that way I can dispense with the design of very high-order filters that resemble ideal filters as much as possible, and use low-order filters... although of course this implies that electronic devices must also be able to handle such high frequencies. A very educational video
Wow, I came to your site to learn PCM which you will cover in part 9 or 10 and here as a bonus you have covered the free DAW software Audacity which as a beginner hobbyist, I actually want to learn to use with my music keyboard and computer. You showed us amazing things Audacity can do much better than sites dedicated to Audacity have shown me. Its like an Oscope and a spectrum analyzer. I want to watch all of your videos.
Audacity is a powerful software for sure! All the best with your learning.
Crystal clear.
Your way of explanation is awesome🔥.Thanks for making this video
You're welcome! Thanks for checking it out..
the quality of your vidoes are so good u def deserve more subs
Thanks mate!
came here from signals-systems & DSP courses, because of stucking in sampling and continuous-discrete conversion. I have to say that, this video is quite good at explaining the subject intuitively and visually. It can be said that you are showing both whole and the pieces of the topic, this is a good approach to explain it.
Sampling-Discretization-Periodization-Modulation, these topics needs to be explained well.
I have still problems on understanding the CT to DT conversion, how this conversion occurs mathematically ?
I mean, how to transform continuous time x(t) to sequence x[n] , mathematically?
what is the operator that converts ""impulse(t) >> to impulse[n] with amplitude of 1"" or ""x(t) . p(t) impulse train >> to x[n] as a sequence""
x(t) . p(t) could be represented as = summation the series of x(nT) . impulse ( t - nT )
But this is still not equal to a sequence of x[n] , because it contains scaled impulses with amplitude of infinity, right?
Therefore I am trying to understand what actually this conversion and this impulse are.
What is the title of topic/video that covers this point?
Thank you for helping.
Great vid made a very complicated subject a bit easier to grasp, still got a lot to learn lol
Cheers mate! Always a lot to learn I'm afraid..
Sampling theorem uses the keyword 'atleast' and we know that we cannot recover signal if we sample exactly at the Nyquist rate as discussed at 8:51.
So shouldn't the theorem state that a band limited continuous time signal can be accurately converted to and from digital signal when sampled at a rate, 'more' than twice as high as the highest frequency component of the waveform?
I have just replaced 'atleast' with 'more'
You're absolutely right. I cringe at it whenever I rewatch this video! It was a mistake.
Thank you for the clarification. Many don't realise this fact and use the expression fs>=2fmax conveniently.
I would also like to thank you for the simplicity and quality of this educational video. Looking forward for more.
These are amazing man
Thanks a lot man!
such a shame I didn't discover this earlier, very well explained, very well produced, thank you!!!
I'm glad you discovered it now!
Excellent presentation. Your videos are so freaking good
Thanks a lot mate! :)
the qualities of this video is extraordinary !!, you deserve more subscriber and views thank you so much
Such a high quality video! Thank you for this, such an enrichment for this platform.
Thanks mate! :)
This video series is seriously amazing!
Thanks very much mate!
Hey, you make learning so easy for me by making these videos. They are well produced, the tempo is perfect, all the necessary information is included and your lecturing style makes it seem like you go through the thinking process alongside us which really makes understanding all this completely effortless. Great great work!
Thank you very much! I'm glad to hear you like the style of the videos. It was an intentional choice to go through all the common questions that I had when learning these concepts and answering them.
@@akashmurthy could you do a series on acoustics?
@@amidall any particular topics in acoustics?
Amazing video! Love the explanations, the visuals and production overall! Subbed.
Thanks for checking it out!
Congratulations, I can sense your dedication. All the best ahead with your new works! 😎👍🏻
omg !! myth busted !! Thanks, loved your teaching a lot.
actually this is so awesome... god bless you.........
Love your effort and time you put in one video, it just phenomenal, i learn a lot from it. Thank you so much
Thanks so much!
Great quality video, super helpful! Thank you
Cheers mate!
I love the way you explain it 💖
The way you work on each topic which seems complex
You are incredible
The graphics and voice are really making it a pleasant learning of joy
Please dont stop 👍
I love the way you put real life into dumb equations .
Thanks a mil for all the kindness!
Incredible stuff!
Thank you so much for the series! You made it so clear and easy to understand, just amazing
You're welcome! Glad you found the series useful!
Thankyou sir
thanks so much! all of this very much applies to sdrs and radio so it is really helpful for me!
Thanks mate! I'm glad it's helpful to you in your domain! First time I heard of SDR today!
Really well done! Concise, clear and correct. Thanks.
Thanks mate!
Bro your videos are so well done thank you
Thanks bro! :)
Simply Genius!!
Very nice video! Thank you very much. Questions to you - why do we need band limiting when the original signal in Audacity is to be created for 3.999KHz ? Where will the high frequencies come from which are to be band limited? And if there are higher frequencies, wouldn't we need to sample w.r.t that value (Fmax will change)? Thanks again.
Amazing work!
you know, your agreat thx for every thing
Thanks sir🥳
Hello, I didn't quite understand the part of leaving a buffer between required frequency and nyquist frequency:
I understand that when converting digital signal back to analog signal, the low pass filter does not perfectly remove all undesired high frequency component, so we have a small portion of signal goes beyond the desired frequency. Whether setting the a buffer or not, this small portion of high frequency signal will always exist (Like for the buffer case you show at 18:56, there is a chunk in the buffer area). I can see that this region is distanced from the nyquist frequency. I don't understand why is it better, because in both scenario (desired signal frequency near 1/2 of sample rate or much lower than sample rate), we both have an undesired chunk.
@@mingzhou2213 Aliasing. I go into more detail on Aliasing in the next videos in the series. But you want to eliminate any frequencies beyong the nyquist, otherwise you run the risk of the the frequencies aliasing and being bounced back into the audible range of the signal. This happens because of the mathematical constraints of discrete signals in a digital system.
Very cool stuff man! loving your tutorials.. Am very glad you have embarked upon this journey.... There's always something new to learn! good stuff.. keep it up! :) cheers
Thanks man! The plan is to continue deep diving into audio concepts and getting as low level as possible while still being engaging and accessible enough. Thanks for the support, and for checking it out!
Awesome video mate thanks for the great work❤
Cheers mate!
Thanks a lot man, this video was really helpful!
Thanks for letting me know!
Thank you so much for these lectures!!
Amazing experience!! the engineering nyquist theorem is enlightening!
Hey I'm glad you found it useful!
awesome!
Thank you for your job.
your videos are amazing.
really super video ....but which software are u using for these animations ??
Thanks! I use Adobe After Effects for most of the animations. For some, I use Processing
Excellent video!
Thank you! :)
May I ask what software you utilized for the sine wave animations? They're. quite brilliant...
thanks for this amazing content
Thank you so much for this tutorial man, I have a kinda stupid question, if the sine wave is a single frequency with no harmonics and is already band limited , why did the 3999 frequency cause aliasing when the sample rate was 8000 Hz when we dont even need a band limiter for this sine wave, is it because it was digital to analog?, because it was produced digitally so it would have an intermediate stage with high frequncies? , and if it was analog to digital would it still cause aliasing ? Again, sorry if its a stupid question but its been bugging me
The minimum required sampling for a 1Hz signal is 2Hz, not 3Hz. As the theorem states AT LEAST twice the highest frequency.
At 2Hz, there's no guarantee that a 1Hz signal will be sampled correctly. If the phase is a particular value, then the signal's sampled points all lie on the zero value position, treating the signal as silenced out.
You are an amazing teacher. Thank you!
Thanks a lot mate!
Excellent lesson, sometimes a little lost coz my english but mostly the visual helps. Just one point to explain, your experience at 8:21.
a tone at 4kHz and a sample rate at 8KHz showing no waveform and producing no sound.
Is it same event when the frequencies = sample rate ? ( for the same example , if we have a tone at 4Khz with a sample rate at 4Khz)
Thank you! So, trying to represent any frequency above the Nyquist will cause the signal to alias. You can check out video #4 Aliasing. But in essense, if you generate a 4kHz signal at a sample rate of 4kHz, the signal will be interpreted as 0Hz. So yes. It will be a very similar result as that of the Nyquist frequency(2kHz).
@@akashmurthy Yes I watched all now. Lot of infos in my brain, but the biggest discovery was about the fact that the sound is reproduced thanks to math and not directly by sample rate, as long as we respect the theorem.
I have two questions if you have time.
1) There is a big discussion in a forum about converting samples. For example with kontakt libraries. They are taking a lot of space (by hundred of GB) , some people convert them to 16Bits and others thinking of even converting to 44.1Khz. I understand that the choice of sample rate and bit depth is more for the recording, but what about sample already digital ? My opinon would be to choose 44.1Khz (coz it's enough) and 24 bits just to avoid plugins "destructing the quality" ( I have read that plugins do that so better to have lot of bits ) and for the dynamic range which looks important. against clipping.
2) One of the explanation of Hi-res is that when you cut at 44.1KHz, you will lose harmonics , timbre and color of the sound. does it make sense ?
thank you and sorry for the long msg
@@josuefox hey, thanks for the questions.
Choosing bit depth is only a consideration when converting from analog to digital or from digital to analog.
Changing the bit depth after a signal has already been sampled does not make a lot of sense. In DAWs, the sample values are represented as floating point values. Plugins use floating point calculations in 32 bit or 64 bits of precision. They rarely ever operate in 16/24 bit fixed point.
And no, down sampling to a rate of 44.1kHz from something higher does not lead to loss of audible harmonics. But it does depend on the quality of the anti Aliasing filter that's doing the conversion.
@@akashmurthy Thank you so much for your answers.
thanks a lot, keep up the good work.
Thanks for checking it out..
very good video.
Amazing video! Thanks for the efforts.
You are gems
The process of recording sound stored in the form of thousands of individual measurement each at a discrete unit of time called..
Thank you for the content dude love em! This is truly valuable!