What is "time resolution"? Options

[Axon]

So I've become involved in a rather colorful argument (I'm Publius in the thread) with somebody on stevehoffman.tv. The original thread revolved around shooting down an old audiophile canard, about how subsample delays cannot be represented in PCM. In the course of that debate, I've begun to question a couple things.

• Is it ever accurate to use the term "time resolution" in any sort of technical context? To the best of my knowledge, it has no universally agreed upon technical definition. Most of the times I've seen it used are either for SACD/DVD-A marketing fluff, or to describe FFT window lengths. I'm tempted to just go quasi-logical-positivist on everybody and say that it is a completely meaningless phrase.
• Is there any meaningful time-domain constraint on audio quality that is directly related to the sampling period? Subsample delays (as I've shown above) are not meaningfully related. Bandwidth is a frequency-domain attribute. Pre-echo potentially gets more audible at lower sampling rates, but this is not a concern with sigma-delta ADCs, and it is of debatable audibility at 44.1 to begin with. Some DSP operations may be harder to implement at lower sample rates, but most of the issues involve seem implementation-related. I'm suspecting that there are no clear general limits as to what can and cannot be accomplished in PCM, except with respect to very domain-specific or system-specific situations; and so any claims of 44khz always being limited in ways different from bandwidth may be regarded with skepticism.

[2Bdecided]

I wish you understood the theory CG, because without it, I can't begin to explain the complete and utter pointlessness of what you're suggesting.

It's a fair enough experiment to ask an undergrad to do in order to practice computer programming and audio processing, but in terms of what it actually tells you about anything, all I can do is just sit here slowly shaking my head!


FWIW, given a random selection of audio signals (real or synthetic) the lower the low pass filter, the further the peaks will move (and, to say the almost same thing differently, the more peaks will completely disappear). The major stumbling block to doing the experiment exactly as you propose will be in determining when a peak has moved vs when a peak has vanished - or, to put it another way, tracking the "same" peak between different versions. Various possible attempts to do this "correctly" (and it will be near-impossible) will mean your results might be unexpected!


The major problem is that every reasonable definition of time-resolution leads to a proof that PCM audio has no issues with time resolution - so now you've invented a new definition in order to prove the opposite. Your success here will not be down to your experiment (which will certainly show some change), but down to your strange definition of time resolution.

Cheers,
David.

[ChiGung]

It's a fair enough experiment to ask an undergrad to do in order to practice computer programming and audio processing, but in terms of what it actually tells you about anything, all I can do is just sit here slowly shaking my head!

Yet you cant explain what is pointless about generating the data described, without indestinct reference to some 'theory' which you believe I dont understand.

Or is there an attempt here...

FWIW, given a random selection of audio signals (real or synthetic) the lower the low pass filter, the further the peaks will move (and, to say the almost same thing differently, the more peaks will completely disappear). The major stumbling block to doing the experiment exactly as you propose will be in determining when a peak has moved vs when a peak has vanished - or, to put it another way, tracking the "same" peak between different versions. Various possible attempts to do this "correctly" (and it will be near-impossible) will mean your results might be unexpected!

I dont need to be informed of possible surprises. I understand very well what you have written there, it is the very situation that I have described repeatedly in this thread re: the 'time resolution' of PCM. I understand what your prefered theoretical statements about 'time resolution' are, and because I have understood what they are not, I have brought the practical situation to your attentions - that the 'spike', the 'radar blip', the 'cymbal peak' etc. cannot be confidently estimated much beyond the sampling interval - [u]precisely because[/i] of the unknown butchery of higher frequency information in the normaly utilised source - the true situation is as you, and as I have described.

Only you consider the true situation completely and utterly pointless to investigate.
And it seems many have felt patronised by my attempts to explain, that it is not utterly pointless to try to correlate actual conditions within record types - that it is in fact how you securely measure such accuracy of correlation. Measuring what is practicaly achieveable in real, normal (not extraneously bandpassed) records.

so now you've invented a new definition in order to prove the opposite. Your success here will not be down to your experiment (which will certainly show some change), but down to your strange definition of time resolution.

My invented definition of time resolution in pcm? - the ability to discern the times of conditions in a pcm record in contrast to the original (natural resolution) material which the pcm is merely a record of.

I think you guys have been mostly presenting the potential 'time resolution' of related partly analogous algebraic systems.

[2Bdecided]

It's a fair enough experiment to ask an undergrad to do in order to practice computer programming and audio processing, but in terms of what it actually tells you about anything, all I can do is just sit here slowly shaking my head!

Yet you cant explain what is pointless about generating the data described, without indestinct reference to some 'theory' which you believe I dont understand.

OK, you're starting with any audio, aren't you? A signal picked up by a microphone, synthetic pink or white noise, etc - correct?

You won't accept pre-filtering of the signal, correct?

And you will low pass filter the signal at varying frequencies, and see how the peaks in the "original" change, correct?

Well think about this: You can start with a 10MHz sampled signal. Given the lack of a filter, there will be something (mainly noise) up to 5MHz. If you filter the signal at 1MHz, some peaks will move a little.

Thus you have proven that a 1MHz low pass filter does something.

So what?!?!?!?!

Cheers,
David.