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#1 |
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Banned
Join Date: Feb 2007
Location: Dublin
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There is a lot of reliance on FFTs in this forum as the final arbiter on comparisons between devices - I have seen statements made that if it's below the noise floor of -120dB then it isn't of importance!
The frequency characteristics seems to always get the focus of attention when analysing audio signals. I would like to draw attention to a paper that has been referenced before "The audibility of the temporal characteristics of audio systems" in which it analysis some aspects of the temporal characteristics of audio as opposed to the frequency characteristics. There are examples given in that paper of different input signals which result in the same FFT spectrum plot. Forgive me if this has been discussed here before but in the threads I have participated in, in which FFT plots have been shown, I have not seen any phase spectrum plots shown only amplitude plots. Last edited by jkeny; 19th February 2011 at 05:00 PM. |
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#2 |
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diyAudio Member
Join Date: Jun 2002
Location: USA, MN
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So, what is the question
Based on your other threads perhaps it is a questioning of measurement vs. perception?FFT's are a tool. Like a hammer, they may be used for good or ill. Just because two signals have the same fft doesn't make them sound the same, I don't think anyone would make that claim. Does that mean that the measurement is useless? No.
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#3 |
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diyAudio Moderator
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I think you are having a terminological problem. "FFT" is not a measurement or a measurement method. It's an algorithm for numerical calculation of the results of a mathematical operator.
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#4 | |
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Banned
Join Date: Feb 2007
Location: Dublin
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Quote:
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#5 |
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diyAudio Member
Join Date: Feb 2003
Location: ..
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(log)magnitude Fourier display has been found exceedingly useful by engineers for a while now
it makes some properties of system measurements easily visible to "educated" human perception/interpretation it is excellent for picking "simply" structured multitone frequencies out of noise - and for detecting correlated errors as "new" frequency components with amplitudes above the noise floor - both intermodulation and harmonic distortions the (log)magnitude display also gives the experienced viewer information about the measurement “quality” – the level, shape of the noise floor, level, frequency of external interference “spurs, “noise skirts” showing source noise properties – all can be used to quickly diagnose test and equipment errors that wouldn’t be as accessible to human perception from a time series plot ( oscilloscope or ADC plot ) to make these judgements you need to know about sample rate, record lenght/bin size, ADC bit resolution but sometimes this inforamation isn't provideded in a graphic - often the point can be made/decerned just with the relative levels at the frequencies of interest even without all of the information the phase information is available for calculation but is not directly "human readable" - because the “noise floor” has "full magnitude" bin-to-bin phase variations making it hard to visually separate "interesting" phase features also the "useful" phase information with the test signals best suited to Fourier analysis is the relative phase between well defined "single bin" frequency components - many "FFT" display software will allow measures between cursor pairs so that you can "navigate" to the relevant measurement pairs where the phase difference is helpful under easy to meet conditions on real world measurements the full “complex valued” magnitude and phase Fourier output is the mathematical “dual” of the Time Series data and contains exactly the same “information” – just arranged differently and which makes some of the “information” easier for humans to “read” Last edited by jcx; 20th February 2011 at 05:40 PM. |
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#6 |
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Banned
Join Date: Feb 2007
Location: Dublin
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Thanks Jcx,
I'm not a user of FFT plots & as I find out more information about it's use as a tool, I tend to want to ask those who use them here, the questions that occur to me. It does make me wonder if these tools are being used appropriately when at least half of the information in a music signal is temporal - maybe even more as the ear seems to have a higher sensitivity in the temporal domain then in the frequency domain. Yet phase information tends to be ignored in most FFT plots posted here. Any idea why? Maybe those who use it as a tool would care also to answer this? |
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#7 | |||
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Banned
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Quote:
Seriously though, for the large part, the magnitude information is what we're interested in. It's true that we tend to pay attention to what we can measure and understand, and the effects of phase changes are less obvious, but a change in phase that is not accompanied by a change in amplitude is difficult to contrive deliberately, never mind it occurring by some coincidence of circuit values, particularly across a range of frequencies. Quote:
No it's not. Phase at the ear changes all the time as you move around. You're just aware that you're moving around, or not, as the case may be... When you move your head, there's a differential change in phase from the lowest frequency to the highest, the high frequencies changing by a whole cycle or more, the low by only a fraction. Quote:
You're just allowing yourself to be overawed. Temporal doesn't mean 'The Enterprise went through a wormhole' It means 'the off-licence is shut' Get yourself some education. I don't mean 'read up on it on the internet', I mean, 'go somewhere they have teachers you can argue with and you have to pass exams.' w |
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#8 |
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diyAudio Member
Join Date: Aug 2010
Location: Sulawesi
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Hello Happy Trollers !
Not many phase plots are shown here, because for measuring accurately the phase with almost all the software available on PC a dual channel measurement ability is required, e.g. a high quality soundcard with stereo input...not the common case. |
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#9 |
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Banned
Join Date: Feb 2007
Location: Dublin
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Are the FFT phase plots not also available from the software using the same original data?
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#10 |
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diyAudio Moderator
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Yes, they are. For non-minimum phase devices (e.g., the vast majority of electronics and components), a Hilbert transform will yield phase data. A complex FFT of the data will yield both real and imaginary parts, from which phase data are also trivially obtained. Phase data are commonly presented in speaker measurements, where non-minimum-phase is common.
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