[paradoxper]

  Is your wallet jittering in anticipation?

I've been looking forward to the Yggy specifically for quite a while, so just a bit. Good thing Yggy isn't priced to be wallet hemorrhaging.

 

[OJNeg]

I read that. That's cool and all but anyone can claim anything sounds better, and all I have read so far is contrarian talk about SD being bad, ASRC being evil, that people with expensive hifi systems are not the target market, mix in some cable skeptic humor etc. No talk of actual performance benefits over conventional optios. Call me unconvinced.

What irritates me is that this anti SD, anti ASRC idea will probably spread and suddenly everone will decide that these technologies are to blame for whatever they subjectively disliked in any particular DAC without any solid argument of causal link.

Mate, we've been complaining about this for a while now.

 

[johnjen]

TGIF eh, JJ?

Heck yeah…
 
But the best part is being able to re-read those 7 paragraphs, whenever the fancy strikes me.
 
There are many memorable meme consolidating themes that just make me break out in laughter, so it’s a desirable thing to do, to be able to induce peals of laughter in a controlled and deliberate manner, whenever the mood strikes me…
 
And I do so enjoy creativity in its many and varied forms of expression.
 
JJ  :thumb

 

[bowerymarc]

   
On the other hand, a very respectable number of Hi-End companies, especially so States side, but not exclusively, have never adopted 1-Bit topologies. Some have done so briefly, only to return to Good Old Fashioned Multi-bit. A notable example is Naim, that have remained steadfastly on the Multibit side, and have only very recently- relunctantly, I am sure- employed Delta-Sigma chips in their latest Digital gear. There must have been very good reasons for this, and certainly not those of economics...

Well, many didn't go for 1-bit because there are problems with 1-bit SD A/D converters which can't be completely solved (limit cycles) that were identified pretty early on.  For D/As there are workarounds.  Lots of papers out there on that topic. But, note that there are many multibit SD converters both A/D and D/A, and anything over 1 bit (some are 1.5 bits..) don't have the limit cycle problem and perform excellently.  The first hi-fi/pro audio A/Ds (dbx) had 6-bit front ends.  There's a distinction between sigma-delta, which is a process of feeding back quantization errors to minimize them, usually 'shaping' the error noise to push it out of the audio band, oversampling, and decimation, meaning reducing the number of bits.  SD uses all of them.  Many hi-bit D/As (meaning, 16+ bits) use oversampling (usually low factors), etc. etc.  Some manufacturers may have reverted back to what they knew.... hey, as long as they're happy with the results, more power to 'em.

 

[Armaegis]

So for those who have been weighing in on the digital filter thingamajigs... what do you guys make of this guy's work: http://www.dddac.com/dddac1794_design.html
He does a PCM1794 NOS with no digital filters

 

[ToddTheMetalGod]

Sorry for bringing this up in a Schiit thread, it's off topic but I don't think it deserves it's own thread. It involves digital playback. How do modern CD players compare to USB DACs? I like to listen to albums all the way through, so I enjoy vinyl albums... so I figure burning my FLAC to CD for use on a CDP would make a good source.

My computer is currently fried, so I'm thinking about getting a Raspberry Pi to replace it until better hardware becomes available, but I think this will open up a can of worms of problems. I found a suitable OS with verified support for many DACs including the Bifrost and my Dragonfly, which helps. So really it is down to quality of CDPs vs DACs. I'm willing to dish out about ~$700 CAD for an extremely good component.

Edit: I'm looking at this Emotiva ERC-3 CDP. It looks like a good quality component. https://emotiva.com/products/sources/erc-3 . It has separate linear power supplies for both the digital and analog sections.

Perhaps I'll get a Bifrost Uber with USB and use my Blu-Ray player as an optical transport until I figure out my computer issues.

 

[davidsh]

If I understood any of the DAC talk it would probably be very exciting etc.. But fankly, I don't 

 

[Anavel0]

This chapter has had the most exciting comments yet. Big thanks to Mike and Jason for taking the time to reply and answer questions. 

 

[paradoxper]

  If I understood any of the DAC talk it would probably be very exciting etc.. But fankly, I don't 

There's still a lot that hasn't been disclosed. So I'm thinking nearer-er production we'll get a further break-down, which should bring more clarity to what Yggy is all about.

 

[XVampireX]

If only they would give us some specs...
 
and if Yggy would support DSD/DXD that would be awesome!
 
I'm still not giving up my Vega.
 
Well regarding the specs, I would love some specs for the Ragnarok.... come on Jason!

 

[judmarc]

But for those of us without a background in DSP design, why is this filter better? Does it have better jitter rejection? After all this I still don't understand what advantage this bit perfect filter represents.

 
Actually it's reasonably simple to understand at a shallow level (which is the only way I "understand" it, so what could be bad about that, right?):
 
All digital filters used in DACs these days (or by software players that take the digital filtering out of the DAC and do it in the computer before the file is sent to the DAC), whether sigma-delta, or R2R or some other variant of multibit, use a type of mathematics called Fourier transforms.  Fourier transforms have this thing called "conjugate variables."  Wotthehellizzat?, you ask?  It's two variables that are related in that they move in opposite directions - as one gets smaller the other gets larger, or as one gets more precise the other gets less precise.  (An electron's position and its momentum are conjugate variables, which is the basis of the uncertainty principle in quantum mechanics.)  For the digital filters in every single DAC or software player now on the market, frequency domain behavior and time domain behavior are conjugate variables.
 
This means as frequency domain behavior of your filter gets better (less distortion from aliasing, for example), the time domain behavior gets worse (ringing).  (If you don't know what aliasing and/or ringing are, not to worry - the basic idea is you'd rather not have either.)  So because these are conjugate variables, every single digital filter currently on the market is the filter designer's idea of a good compromise between frequency domain and time domain optimization, since right now you can't have both.
 
What Mike's done is step outside this whole problem that everyone's been wrestling with for a couple of decades and said "We don't need no steenkin' Frenchy math!"  (Well, no, I doubt he said anything like that, but anyway....)  He's designed/designing (don't know whether he feels he's done yet) a filter using math that doesn't have this conjugate variable dilemma, so that it can, in his words, be "optimized for...time and frequency domain."
 
Hope that helps.

 

[davidsh]

That sounds clever... or something 

 
Thank you.

 

[drez]

Actually it's reasonably simple to understand at a shallow level (which is the only way I "understand" it, so what could be bad about that, right?):

All digital filters used in DACs these days (or by software players that take the digital filtering out of the DAC and do it in the computer before the file is sent to the DAC), whether sigma-delta, or R2R or some other variant of multibit, use a type of mathematics called Fourier transforms.  Fourier transforms have this thing called "conjugate variables."  Wotthehellizzat?, you ask?  It's two variables that are related in that they move in opposite directions - as one gets smaller the other gets larger, or as one gets more precise the other gets less precise.  (An electron's position and its momentum are conjugate variables, which is the basis of the uncertainty principle in quantum mechanics.)  For the digital filters in every single DAC or software player now on the market, frequency domain behavior and time domain behavior are conjugate variables.

This means as frequency domain behavior of your filter gets better (less distortion from aliasing, for example), the time domain behavior gets worse (ringing).  (If you don't know what aliasing and/or ringing are, not to worry - the basic idea is you'd rather not have either.)  So because these are conjugate variables, every single digital filter currently on the market is the filter designer's idea of a good compromise between frequency domain and time domain optimization, since right now you can't have both.

What Mike's done is step outside this whole problem that everyone's been wrestling with for a couple of decades and said "We don't need no steenkin' Frenchy math!"  (Well, no, I doubt he said anything like that, but anyway....)  He's designed/designing (don't know whether he feels he's done yet) a filter using math that doesn't have this conjugate variable dilemma, so that it can, in his words, be "optimized for...time and frequency domain."

Hope that helps.

Thanks, best explanation I could hope for. Sounds promising.

 

[ab initio]

   
Actually it's reasonably simple to understand at a shallow level (which is the only way I "understand" it, so what could be bad about that, right?):
 
All digital filters used in DACs these days (or by software players that take the digital filtering out of the DAC and do it in the computer before the file is sent to the DAC), whether sigma-delta, or R2R or some other variant of multibit, use a type of mathematics called Fourier transforms.  Fourier transforms have this thing called "conjugate variables."  Wotthehellizzat?, you ask?  It's two variables that are related in that they move in opposite directions - as one gets smaller the other gets larger, or as one gets more precise the other gets less precise.  (An electron's position and its momentum are conjugate variables, which is the basis of the uncertainty principle in quantum mechanics.)  For the digital filters in every single DAC or software player now on the market, frequency domain behavior and time domain behavior are conjugate variables.
 
This means as frequency domain behavior of your filter gets better (less distortion from aliasing, for example), the time domain behavior gets worse (ringing).  (If you don't know what aliasing and/or ringing are, not to worry - the basic idea is you'd rather not have either.)  So because these are conjugate variables, every single digital filter currently on the market is the filter designer's idea of a good compromise between frequency domain and time domain optimization, since right now you can't have both.
 
What Mike's done is step outside this whole problem that everyone's been wrestling with for a couple of decades and said "We don't need no steenkin' Frenchy math!"  (Well, no, I doubt he said anything like that, but anyway....)  He's designed/designing (don't know whether he feels he's done yet) a filter using math that doesn't have this conjugate variable dilemma, so that it can, in his words, be "optimized for...time and frequency domain."
 
Hope that helps.

I don't think this is mathematically accurate. The uncertainty principal holds whether or not you choose to think of a signal in time-domain or frequency-domain. You can't be localized  in both time AND frequency --- simply not mathematically possible. The frustrations with using fourier analysis, where signals are broken down into a sum of sine modes (sine modes have infinite extent in time and are perfectly localized in frequency) led to the development of methods such as wavelet analysis, where one can use a different set of test signals to (i.e., wavelets) to decompose a time domain signal. here, Wavelets have some localization in time and some frequency content; however, they too cannot be localized in both time AND frequency.
 
Digital filters are not usually implemented using any sort of direct application of fourier transforms on the signal. One would need the entire waveform to transform, manipulate, and inverse transform back to the time domain. DSP use finite impulse response filters (which use a finite number of samples to filter) or infinite impulse response filters (which use feedback). Fourier techniques can be implemented on small chunks of the signal at a time. In this case, the windowing of the data introduces spectral artifacts because of the truncated signal. Fourier methods would best be applied as a post-processing techinque where the entire waveform in available all at once. In streaming audio applications it runs into windowing problems because of truncation.
 
Cheers

 

[judmarc]

  I don't think this is mathematically accurate. The uncertainty principal holds whether or not you choose to think of a signal in time-domain or frequency-domain. You can't be localized  in both time AND frequency --- simply not mathematically possible. The frustrations with using fourier analysis, where signals are broken down into a sum of sine modes (sine modes have infinite extent in time and are perfectly localized in frequency) led to the development of methods such as wavelet analysis, where one can use a different set of test signals to (i.e., wavelets) to decompose a time domain signal. here, Wavelets have some localization in time and some frequency content; however, they too cannot be localized in both time AND frequency.
 
Digital filters are not usually implemented using any sort of direct application of fourier transforms on the signal. One would need the entire waveform to transform, manipulate, and inverse transform back to the time domain. DSP use finite impulse response filters (which use a finite number of samples to filter) or infinite impulse response filters (which use feedback). Fourier techniques can be implemented on small chunks of the signal at a time. In this case, the windowing of the data introduces spectral artifacts because of the truncated signal. Fourier methods would best be applied as a post-processing techinque where the entire waveform in available all at once. In streaming audio applications it runs into windowing problems because of truncation.
 
Cheers

 
See http://resonessencelabs.com/digital-filters/ (the folks who led the ESS SABRE DAC chip project - they know something about math and digital filters) for more detail.
 
The uncertainty principle in quantum mechanics has to do as I noted with particle position and momentum as the conjugate variables, not frequency domain and time domain behavior.  I used it as another example of conjugate variables under Fourier analysis - as position becomes more precisely known, momentum becomes less precisely known, and vice versa.  For the same reason (because they are conjugate variables), with digital filters as time domain behavior becomes more optimized, frequency domain behavior becomes less optimized, and vice versa.