Converting Analog Data to Binary, Sampling, Quantization - AP Computer Science Principles
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- Опубліковано 24 сер 2024
- Strap in, this one's gonna get a bit bumpy.
Converting from analog data to digital is a three step process. "Sampling" involves taking a sample of points from a continuous curve, such as a sound wave. Once the points have been selected, their values must be rounded off in a process called "quantization." Finally, these approximated values are further simplified, then converted into binary.
As you watch, keep these two facts in mind:
1) Analog data is infinite, digital is finite.
2) Lower intervals mean higher fidelity, but also a larger file.
Khan Academy Article:
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SUPER Lecture! Just what I needed to shed light on this subject. THX!
Excellent lecture Dr. Cunningham. Very clear & concise with a more modern, youthful, & invigorating tone plus using audio as an application motivator. ... I couldn't have done any better myself.
Thank you so much! I am doing the AP Computer Science course on Khan Academy. Your video's always help me understand things better!
Glad to hear it!
@@professorcunningham8106 Do you plan to make more video's on the AP Computer Science course on Khan?
@@nathanielstubbs0005 Yep! Unfortunately, I work full time as a teacher, so I don't get to make these as often as I'd like, but more are on the way when I have the time!
thank you ! Khan academy's content in this particular topic is little complex for me but you explain in a very smooth way ! THANKS TO PROFFESOR CUNNINGHAM
Thank you for the feedback! I was honestly worried this would be too dense
Great explnation!
Very well explained. I've checked out numerous explanations on this topic for how accurate the analogue signal relates to the reconstructed signal and professionals including and electronics expert all day that that the analogue signal is exactly the same coming out as going in. Yet in your breakdown the reconstructed signal can only ever be an approximation and that the process of rounding also means that it's not exact. I know in audio that with the amount of sampling and bit depth that the reconstruction may be very close but it can't be exact. I was also looking for how this process of ad-da reconstructs the curve of the signal and this is the first time I've heard, in your words, that it is an estimation, which would mean another lacking exactitude! I've often wondered how thousands of harmonics in an audio signal is affected by this analogue to digital and back again process ( not thinking of Nyquist here) in its processing ability to reconstruct it all faithfully. Of course there's the filter roll off depending on sampling rate, 44.1, 48, 96, that can affect aliasing etc
In the world of audio perhaps it doesn't matter these days with enough sampling rate and bit depth that you get very high quality music. Yet to me it's always had a slightly different sound from an original analogue source (forgetting analogue recording formats for a mo) noticing years ago when digital mixing desks took over from analogue. I suppose because ad-da is a process it's bound not to remain identical. But very useful these days. Anyway, I enjoyed your explanation of this process.
Thank you sir
Thank you so much!
This video helped me a lot.
This helped me so much that I was able to sleep tonight. Thank you.
thank you, it is a great help.
Great walk-through!
thank you so much youve helped me so much
Thank you, learned a lot and just subscribed to your channel.
When encoding, we only change the values of y to binary. Additionally, there will be many x values. At the quantized y value (at this particular point), I didn't understand how the computer reads the values of x and y and reconstructs them. Could you explain?
Both x and y are being converted to binary. Recall that ALL data that passes through a computer is represented in binary. As for how the computer reconstructs the original X and Y, that would rely on some code providing the baseline. For example, If I know that the minimum voltage was 50 volts, and I set up the code so that 50 was my baseline, the computer would simply add 50 to any number I provided, so a value of 010, which translates to 2, could be read as 52. This allows us to compress the number of bits needed to store the data losslessly.
I don't know if that helps, but it's the best I've got for the moment. I'd love for any other computer science students or teachers to weigh in here.
It's good.
Can you come work at my university and teach my class please? 🥹
I'd love to, but probably not