HOLMImpulse: Measuring Frequency- & Impulse-Response - Page 51 - diyAudio
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Old 16th October 2009, 01:43 PM   #501
breez is offline breez  Finland
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Quote:
Originally Posted by askbojesen View Post
Thanks, ARTA "2.3 Frequency Resolution of DFT and Octave-Band Analyzers"
if ARTA window = BLACKMANN3, then this corresponds to HOLMImpulse amplitude smoothing with N = 1, N = 3

The HOLMImpulse FR makes a calculation for all discrete frequencies, not only the ISO-standard-steps. I might implement an ISO-standard-step FR which will show bars and not a curve.
The discussion on windows, however, refers to the DFT resolution. The 1/N smoothing is discussed further down in that section with methods similar to Earl's (continuous smoothing).
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Old 16th October 2009, 01:46 PM   #502
gedlee is offline gedlee  United States
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Quote:
Originally Posted by askbojesen View Post
1. When you sum the RF - is it then a complex sum? or do you sum the amplitudes?

2. When you use your weighting function - do you multiply with 1/f to compensate for your equidistant frequencies?
I sum the "magnitudes", and yes, you must do a 1/f compensation for the frequencies, but this is part of the "integration".
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Old 16th October 2009, 01:51 PM   #503
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Originally Posted by breez View Post
The discussion on windows, however, refers to the DFT resolution. The 1/N smoothing is discussed further down in that section with methods similar to Earl's (continuous smoothing).
Sorry, Yes I are right - he writes:
Power output of 6-pole Butterworth bandpass filter First, the power spectrum is weighted with a squared magnitude of a bandpass filter response.

And not which bandpass filter he uses.

If I get the time and feel for it I can compare my amplitude smoothing with this
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Old 16th October 2009, 01:56 PM   #504
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Default gedlee = askbojesen?

Quote:
Originally Posted by gedlee View Post
I sum the "magnitudes", and yes, you must do a 1/f compensation for the frequencies, but this is part of the "integration".
Then your post processing should equal my amplitude smoothing.

I suggest the following for a measurement:

1. Export unsmoothed FR or IR to your program
2. Your program -> Smoothed FR/IR -> HOLMImpulse
3. Compare

Perhaps you can email me an IR and your smoothed FR - then I can do the comparison?
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Old 16th October 2009, 03:29 PM   #505
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Originally Posted by askbojesen View Post
Still a problem?
Got it. I hade to update my Adobe reader.
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Old 16th October 2009, 03:54 PM   #506
gedlee is offline gedlee  United States
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Quote:
Originally Posted by askbojesen View Post
Then your post processing should equal my amplitude smoothing.

I suggest the following for a measurement:

1. Export unsmoothed FR or IR to your program
2. Your program -> Smoothed FR/IR -> HOLMImpulse
3. Compare

Perhaps you can email me an IR and your smoothed FR - then I can do the comparison?
How can I import a FR curve? is there documentation of the proper format? After smoothing the FR curve is purely real there is no phase. Is this a problem?

If I smooth in Holm, can those curves be exported en-mass like the IRs?
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Old 16th October 2009, 07:58 PM   #507
JohnPM is offline JohnPM  United Kingdom
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Originally Posted by gedlee View Post
I take the impulse response and find the FR, normal FFT. Then I go to a set of log spaced frequencies and at each of those find a weighting function that is 1/N wide - I use a gaussian type of shape. The magnitudes at each of the FFT data point is then weighted by this shape and integrated (summed). This procedure has trouble at LF when the frequency spacing of the data is comparable to the smoothing bandwidth, but works good otherwise.
Instead of using a gaussian window use a rectangular window but make 4 successive passes through the data. It is orders of magnitude more efficient (when correctly implemented) and is easily implemented as a sliding window (whose endpoints can vary logarithmically as you go for fractional octave filtering) for more accurate filtering.
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Old 16th October 2009, 08:10 PM   #508
gedlee is offline gedlee  United States
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Instead of using a gaussian window use a rectangular window but make 4 successive passes through the data. It is orders of magnitude more efficient (when correctly implemented) and is easily implemented as a sliding window (whose endpoints can vary logarithmically as you go for fractional octave filtering) for more accurate filtering.
Sounds interesting, could you ellaborate further. It would be way more efficient and I need that, but I am unclear on why multiple pass makes any difference, or exactly what you mean.
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Old 16th October 2009, 10:44 PM   #509
JohnPM is offline JohnPM  United Kingdom
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The second pass is equivalent to a triangular weighting function, successive passes approach ever closer to a gaussian function. See this link for details: Relatives of the Moving Average Filter. That is the method I use for the fractional octave filters in REW.
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Old 17th October 2009, 12:47 PM   #510
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From a numerical analysis point of view smoothing always reduces to some form of integration:

A'(fc) = integral [W(f)A(f)]/ integral[W(f)] over some limits f1 to f2 where fc is between them. W(f) is a weighting function of choice, typically symmetric about fc. Obviously, in the digital domain the integrals are replaced with their representative summations.
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