Advantage of 24 vs 16 bit, a primer...

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mshilarious said:
It's a different principle--each subsequent bit changes the previous voltage level. So whereas in PCM you know that a discrete sample is a given voltage, with DSD you don't really know much at all without referencing the surrounding bits.
Correct me if I'm wrong here - which I could very well be - but isn't DSD just "transactional processing"; i.e. each sample is reporting the change in amplitude from the previous sample instead of an absolute amplitude? While this is indeed looking at the values from a different perspective, the "resolution" that the bits represent doesn't change from sample to sample; flipping bit X in sample 133 represents the same change in voltage that flipping that same bit in sample 734 does, regardless of what the values of the previous sample may be. They still represent an absolute value of change, do they not?

These values may be different than the values expressed in PCM encoding, but it's still an absolute scale; it's just returning a value of the change in amplitude between samples instead of the value of the intrinsic amplitude of the discrete sample. Or do I have that misunderstood as well? (I probably do. :o )

Also - and I'm going out on a speculative limb here - I would think that the properties of the binary math remain the same between DSD and PCM; that a 16-bit value in PCM has the same range and resolution as a 16-bit value in DSD.

Please correct as needed :)

G.
 
SouthSIDE Glen said:
Correct me if I'm wrong here - which I could very well be - but isn't DSD just "transactional processing"; i.e. each sample is reporting the change in amplitude from the previous sample instead of an absolute amplitude? While this is indeed looking at the values from a different perspective, the "resolution" that the bits represent doesn't change from sample to sample; flipping bit X in sample 133 represents the same change in voltage that flipping that same bit in sample 734 does, regardless of what the values of the previous sample may be. They still represent an absolute value of change, do they not?

Sounds right. But for example in PCM I can call 4 subsequent -0dBFS samples a clip, but 256 (or whatever the correct number) subsequent 0 bits in DSD is :confused:


Also - and I'm going out on a speculative limb here - I would think that the properties of the binary math remain the same between DSD and PCM; that a 16-bit value in PCM has the same range and resolution as a 16-bit value in DSD.

Please correct as needed :)

G.

To get a 16-bit "DSD" value you'd have to decimate, which makes it PCM. Once you accept that decimation must occur at some point in the chain, since practically nobody is doing DSD processing, then it's just a question of whether anti-imaging should be done at the mastering or consumer level :confused:

Personally, I would guess anybody who claims 24/96 PCM is better or worse than DSD is probably smoking some weird wild weed. But I don't really know, so I'll just add this smiley ------> :confused:
 
gullfo said:
the larger number is significantly less impacted than the smaller number - hence the "resolution" on the larger number if better.
This is exactly what I've attemtped to prove in previous posts. I know this already. What I am saying is that, after the digital waveform is recreated in the analog realm, none of this resolution stuff is going to have the kind of effect on sound we might intuitively expect it to. The fact that there is only a set number of discrete values to map a bit to does not necessarily mean that volume level of a WAVEFORM at any particular point, even for a very short period of time, will be limited by this resolution to being moved in its location to the "nearest discrete level" perscribed by the bits. I think basic Nyquist theory takes care of that.

and if we take low level 16 bit and try to raise it, guess what? we're effectively raising the distortion level because we're taking less resolution data and moving up into a more audible region.
HTH

Ah see, you've helped me explain my point right here.
You are effectively rasing the distortion level relative to the signal, because the signal is now closer to the level of quantization error (-96db).
This is why I've said the only thing that really needs to be discussed in theory is the limited dynamic range - this number is a way of describing the effect that limited resolution has on the sound. We only really need to throw this one number out there and stop thinking about the resolution 'steps' in the way that we have.
 
SouthSIDE Glen said:
which by it's very definition has an inherant percentage of error built into it because the digital words are of finite length
Ok... sort of. As long as we are thinking about this "error" in the same way. Re: my above post.

There will be some "smoothing" - a form of noise -
Whoa, hold it there. The only smoothing going on is from the antialiasing filter. This is not a form of noise. It is the removal of frequencies above Nyquist. A wave that digitally looks like a triangle at 20Khz will be turned into a pure sine at 20Khz. No noise required.

From that point on I'm afraid I didn't really understand the rest of your post.
 
bleyrad said:
This is exactly what I've attemtped to prove in previous posts. I know this already.

yes, I was supporting you, just trying to explain it a bit differently so people have a chance to grasp this a bit better...
 
mshilarious said:
To get a 16-bit "DSD" value you'd have to decimate, which makes it PCM.

basically a transposition function + a calculation on the offset of the previous value to define a "full value". one weakness (unless a checksum is involved) would be a loss in the DSD stream where it cannot correctly judge the offset value previously stated... must be some logic to hold the level over some number of bits to avoid this possiblity...
 
bleyrad said:
Whoa, hold it there. The only smoothing going on is from the antialiasing filter. This is not a form of noise.
Erroneous or misunderstood on both points.

The purpose of the DAC is transfroming quantized data into a linear waveform. That, by definition, is a form of smoothing. Your own description of a rounding error is an inadvertant form of smoothing.

Using the classic definition of noise as any modification of the original data not resulting in a net gain of informational content, ADC is by definition adding noise to the signal by approximation. You'd have to have an infinite number of bits sampling at an infinitely fast frequency for this process to be noise free.

While it could be argued that the intra-sample extrapolation performed during DAC is adding information, and is therefore not noise by the strict definition, the fact remains that such information is a synthesized "guess" as to how to fill in that information, and compared to the original analog signal it could be called noise in the fact that it is falsely representing itself as a copy of the original, which it is not. And turning a digital representation of a triangle wave into an analog sine wave is most certainly noise.

I'm not even talking about stuff like filtering off aliasing or stuff like that. I'm talking about the error (read: noise) inherent in the conversion between analog and digital and back again. If those errors infest the data even one bit beyond the least signifigant bit of the digital word, it can be said that those errors are at a noise level greater than the theoretical noise level defined by the word itself.

Put bluntly, it is possible for the A/D//D/A conversion process to operate at a higher noise level than what is theoretically (read: mathematically) possible by the definition of the size of the digital data stream itself. In the real world a 16-bit scheme would never truely attain a full 96dB range if the conversion process itself injects a few dBFS worth of noise into the stream.

All my point meant to be was that this does not render discussion of the "resolution" of any given digital scheme as meaningless. The higher the bit width, the higher the overall signal resolution, regardless of noise induced in the conversion process.

In fact dynamic range and resolution are actually two descriptions of the same property; much like electricity and magentism. I'll grant you that, unlike electricity and magentism, perhaps here the fact that they are two faces of the same head renders discussion of resolution somewhat redundant, and therefore discardable. But I only understand that that now after this conversation. :). I didn't grasp that 24 hours ago :).

However, I do still have a bit of (perhaps semantic) disagreement with this passage of the conversation:

bleyrad said:
gullfo said:
and if we take low level 16 bit and try to raise it, guess what? we're effectively raising the distortion level because we're taking less resolution data and moving up into a more audible region.

Ah see, you've helped me explain my point right here.
You are effectively rasing the distortion level relative to the signal, because the signal is now closer to the level of quantization error (-96db).
You are not "raising" the distortion level at all when you do this. All you are doing is increasing the number of bits by which the origial digital value is represented. In essence, the "resolution" of the data has increased, but the amount of error/noise/distortion has not.

By moving it "up" in the position of a larger word you are increasing the volume of the signal and therefore making it more audible to the human ear. This is of course ultimately important, but it should be understood that this is happening because of a shift in position (effectively a change in represented volume), not because of an increase of noise in the data.

G.
 
SouthSIDE Glen said:
Using the classic definition of noise as any modification of the original data not resulting in a net gain of informational content, ADC is by definition adding noise to the signal by approximation.
OK, here we go. This is the core of the misunderstanding here I think. To me, this is distortion, not noise. AFAIK noise is a a random, spurious, continuous signal independent of the real signal content. What you are talking about is distortions (changes) of the actual signal, or additional false signal being introduced which is signal-dependent . This is quantization distortion.

You'd have to have an infinite number of bits sampling at an infinitely fast frequency for this process to be noise free.
Distortion free. Agreed on the first point (sampling bits), for the most part. Not in agreement on the second point (infinite sampling frequency) unless the goal is infinite bandwidth - not even remotely a practical concern in audio.

While it could be argued that the intra-sample extrapolation performed during DAC is adding information, and is therefore not noise by the strict definition, the fact remains that such information is a synthesized "guess" as to how to fill in that information, and compared to the original analog signal it could be called noise in the fact that it is falsely representing itself as a copy of the original, which it is not.
OK, no offense or anything, but reading this paragraph says to me that you are not fully up to speed on Nyquist theory. Please correct me if I'm wrong and just misinterpreted this somehow.
The idea is that, given the absence of any electrical or filter limitations, what goes in can be EXACTLY what comes out in digital, up to the Nyquist frequency. No distortions or noise of any kind - this is theoretically possible. It doesn't take infinite bit depth or sampling frequency. All these do is add a few conditions as to what the source material must be in order to be 100% accurately reproduced in the digital realm: 1) You cannot expect to reproduce frequencies higher than half the sampling rate, and 2) You cannot expect a distortion-free signal if it exists at or around the limit of dynamic range.
If these two conditions are met/acceptable then you can expect to have yourself a fully accurate, fully transparent copy of the original signal coming out your theoretically-perfectly-designed DAC. The math is beautiful.

And turning a digital representation of a triangle wave into an analog sine wave is most certainly noise.
I'm not even talking about stuff like filtering off aliasing or stuff like that.
This doesn't jive. When you talk about turning a triangle into sine, ALL that you are talking about is filtering. The original content UP TO THE NYQUIST FREQUENCY is completely untouched - and the stuff above it is just thrown away.
Funny thing is, if the DAC didn't do it, and the speakers didn't do it, our ears would turn it into a sine for us. If you could somehow play a 20Khz square wave accurately, it would sound exactly the same to us as a 20Khz sine wave (assuming you can hear that high).

Put bluntly, it is possible for the A/D//D/A conversion process to operate at a higher noise level than what is theoretically (read: mathematically) possible by the definition of the size of the digital data stream itself. In the real world a 16-bit scheme would never truely attain a full 96dB range if the conversion process itself injects a few dBFS worth of noise into the stream.
You lost me here, mostly because your usage of "noise" is really confusing to me.

You are not "raising" the distortion level at all when you do this. All you are doing is increasing the number of bits by which the origial digital value is represented. In essence, the "resolution" of the data has increased, but the amount of error/noise/distortion has not.
Maybe it wasn't obvious, but this was exactly what I was trying to say. That's why I used the words "effectively" and "relative" in there. :)
 
From the DSP classes I have taken I would have to agree with bleyrad.

As long as your original signal is limited to between 0Hz and the Nyquist frequency, you won't lose any frequency content.

And noise (or distortion) is limited to your bit depth per sample. If you had an infinite # of bits, there would be no noise/distortion.

Also, the interesting thing about the triangle wave example, is that it's not the D/A throwing away the higher frequencies turning it into a sine wave. It's actually the anti-aliasing filter before the A/D that throws away the frequencies above the Nyquist frequency before the A/D can get "confused" by the high frequencies. This "confusion" is called aliasing. To the A/D, a frequency that is "x" Hz above the Nyquist frequency "N" also looks like N-x Hz.

So N+x looks like N-x, or if Nyquist is 20kHz then 25 kHz looks like 15 kHz to the A/D without an anti-aliasing filter.

(And the filter after the D/A is called the reconstruction filter.)
 
So... not to interrupt... but, would the maximun number of indvidual ways that cd quality audio could sound like in a one second clip be, ~2,866,500,000? (by multiplying 65000 for the number of discreet steps per sample by the sample rate of 44.1khz). And couldn't you multiply that by it's self so that the maximum number of ways that a 3 minute song could sound would be 2,866,500,000 to the 180th power. Couldn't you then have super computers map out each possible 3 minute song? (in theory?)
 
I think it's more than that. The # of combinations possible in a second would be 65,535 to the 44,100th power. So a # with something like 160,000 zeros. Just for 1 second of data.

Of course most of those combinations would be noise.

earthboundrec said:
So... not to interrupt... but, would the maximun number of indvidual ways that cd quality audio could sound like in a one second clip be, ~2,866,500,000? (by multiplying 65000 for the number of discreet steps per sample by the sample rate of 44.1khz). And couldn't you multiply that by it's self so that the maximum number of ways that a 3 minute song could sound would be 2,866,500,000 to the 180th power. Couldn't you then have super computers map out each possible 3 minute song? (in theory?)
 
no shit huh? That's insane. So you take x to the the 160,000 power and put that number to the 180th power for the total possible amount of ways that cd quality audio can sound in 3 minutes. Fuckin' crazy.
 
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