But our hearing is based in time to frequency domain conversion, so we suffer all that lack of precision too
btw: I never expected the non-sense to go so far
not exactly true...
it would mean that we can measure a frequency but
not a time interval..
music is frequencies AND time intervals (rythme)
and we hear the two, although at different accuracy degrees
for each...
Lumba,
You are quite right about the frequency-time relationship, although it may be a stretch to suggest that the relationship stems from the Heisenberg uncertainty principle. Something that is narrow in time is wide in bandwidth; something that is narrow in bandwidth is wide in time.
Yes, music is complex, but you are throwing the baby out with the bathwater. You are just throwing up your hands, suggesting that because something is hard to analyze or imperfect, we should just give up on getting as much out of our analysis as we can. I completely disagree with this approach. You're saying, its too hard to analyze and do engineering, so lets just throw something together and listen to it.
We need to understand, analyze and engineer and measure the best we can, then listen to it, then iterate, recognizing that all of these steps are not without limitations.
Cheers,
Bob
I agree.
We shouldn't diiscard the frequency domain completely - that's what we have got so far. It is only a not so good approximation of the "reality".
Time measurements are king, this should be clear (but it's not).
lumba, the music signal is a sum of sinus functions...
whatever the time interval of measurement...
so all an amplifier as to do is to be able to reproduce
correctly the faster slewing voltage that a musical signal
can produce, in the desired dynamic range and with
enough gain accuracy...
it s not that difficult to implement, and there s countless
amplifiers that do the job well..
as you pointed, there s far more to gain with
speaker improvements....
correctly the faster slewing voltage that a musical signal
can produce, in the desired dynamic range and with
enough gain accuracy...
it s not that difficult to implement, and there s countless
amplifiers that do the job well..
as you pointed, there s far more to gain with
speaker improvements....
Hi,
the Fourier transform will analyze pure sine waves perfectly representing a well-defined frequency. The Fourier transform may be useful for analyzing other signals in different applications fields, but music signals are very far from sine waves, it just has to give up pretty quickly.
Huuum, audio sinusoidal signals are not like all others. Seems to me a new theory, maybe a Nobel going on. At least he is near the Nobel comission...less costs on receiving the prize.
the Fourier transform will analyze pure sine waves perfectly representing a well-defined frequency. The Fourier transform may be useful for analyzing other signals in different applications fields, but music signals are very far from sine waves, it just has to give up pretty quickly.
Huuum, audio sinusoidal signals are not like all others. Seems to me a new theory, maybe a Nobel going on. At least he is near the Nobel comission...less costs on receiving the prize.
No, Lumba, you are the guy here that is saying this lot of b*** s**t, not me.
You have to enlight the people here, not me.
regards,
"Hi,
just shortly,
the Fourier transform (provides a linear time-frequency representation, expressing one-dimensional signals with a single formula, in which frequencies are constant over time) is based on the uncertainty (Heisenberg inequality) principle that states: the more precisely the position of a particle is determined, the less precisely the momentum is known in this instant, and vice versa. The processed signal can be either analyzed with good time resolution or good frequency resolution. Again, music signals are extremely complex, totally varying in nature (frequency, amplitude and phase, full of short-duration transients and bursts containing an infinitely dense packing of an infinite number of frequencies; an impenetrable jungle, a nightmare for any analyzing method. In my opinion, the degree of inaccuracy renders the analysis worthless."
Rubbish.
Good engineering - in any field - is about making sensible tradeoffs, using imperfect materials and knowledge at the time, to create SOTA solutions to difficult problems. All this ** about feedback being bad, inadequate analytical tools, imperfect components, layers unfathomable complexity in music signals etc etc is a smokescreen for people who don't want to spend some effort doing practical, real world engineering to produce something of value that can be scrutinized and assesed comparatively by their peers in practical terms.
just shortly,
the Fourier transform (provides a linear time-frequency representation, expressing one-dimensional signals with a single formula, in which frequencies are constant over time) is based on the uncertainty (Heisenberg inequality) principle that states: the more precisely the position of a particle is determined, the less precisely the momentum is known in this instant, and vice versa. The processed signal can be either analyzed with good time resolution or good frequency resolution. Again, music signals are extremely complex, totally varying in nature (frequency, amplitude and phase, full of short-duration transients and bursts containing an infinitely dense packing of an infinite number of frequencies; an impenetrable jungle, a nightmare for any analyzing method. In my opinion, the degree of inaccuracy renders the analysis worthless."
Rubbish.
Good engineering - in any field - is about making sensible tradeoffs, using imperfect materials and knowledge at the time, to create SOTA solutions to difficult problems. All this ** about feedback being bad, inadequate analytical tools, imperfect components, layers unfathomable complexity in music signals etc etc is a smokescreen for people who don't want to spend some effort doing practical, real world engineering to produce something of value that can be scrutinized and assesed comparatively by their peers in practical terms.