HOLMImpulse: Measuring Frequency- & Impulse-Response

[tms0425]

Originally Posted by askbojesen

Still a problem?

Works for me

[gedlee]

Originally Posted by askbojesen

How do you smooth?

Please reveal your formulas, so I can implement your method

I average the magnitudes of the frequency bins as a weighting filter is swept through the frequency response data. Its not very efficient and I'd like a better method, but it does work.

I plan to try yours as well.

[gedlee]

Originally Posted by Key

I just am not sure about a lot of things which people claim are audible. My system seems to be immune to all types of things most experts claim should be audible. But I am still testing so no conclusions on group delay and diffraction effects yet.

I find that most things that the "experts" claim are audible aren't. But then most of their tests for audibility of things aren't sufficiently well controlled to be useful for making any kind of judgement. My tests are all double blind with a lot of subjects.

[askbojesen]

Originally Posted by gedlee

I average the magnitudes of the frequency bins as a filter is swept through the frequency response data. Its not very efficient and I'd like a better method, but it does work.
I plan to try yours as well.

Isn't this what is called stepped sine method?

What when you measure your polar-patterns using impulse responses from HOLMImpulse?

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Well, I do not claim to have the correct smoothing formula. I now have 4 methods:
A. No smoothing, no window
B. Time-window
C. Absolute log-smoothing (I use this for digital room-adaption)
D. Complex log-smoothing <=> Frequency dependent window

Personally I don't see the advantage of D for correcting speakers (this is my goal) or making room-adaption. A lot of other measurement software implement D in a not flexible and transparent way, so I find it nice to see what I'm doing in the time-domain.

I need to make a careful comparison with pink noise power response and stepped sine.

[gedlee]

Originally Posted by askbojesen

Isn't this what is called stepped sine method?

What when you measure your polar-patterns using impulse responses from HOLMImpulse?

----------
Well, I do not claim to have the correct smoothing formula. I now have 4 methods:
A. No smoothing, no window
B. Time-window
C. Absolute log-smoothing (I use this for digital room-adaption)
D. Complex log-smoothing <=> Frequency dependent window

Personally I don't see the advantage of D for correcting speakers (this is my goal) or making room-adaption. A lot of other measurement software implement D in a not flexible and transparent way, so I find it nice to see what I'm doing in the time-domain.

I need to make a careful comparison with pink noise power response and stepped sine.

No its not stepped sine, thats different.

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.

There is no "absolute" correct method - all measurements of loudspeakers are evolving, but its important to understand how and why they all might differ.

[DSP_Geek]

Originally Posted by gedlee

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.

Above a few hundred Hz the ear's critical bandwidth is measurable in logarithmic terms such as fractions of an octave, but below this the critical bands approach constant frequency width the lower you go. Karjalainen et al in JAES (Journal of the Audio Engineering Society) Vol 47 No. 1/2 show a filter structure for speaker correction taking this aural characteristic in mind, which shows improved performance in the lower frequencies.

[askbojesen]

Originally Posted by gedlee

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.

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?

[breez]

ARTA manual describes the smoothing methods used by ARTA, which may be of interest to this discussion. Section 2.3. ARTA home

[askbojesen]

Originally Posted by breez

ARTA manual describes the smoothing methods used by ARTA, which may be of interest to this discussion. Section 2.3. ARTA home

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.

[soongsc]

I've always been curious as to why not just use a rectangular time window and smooth only the portion outside the window? The part outside the window certainly should not have certain frequency content, and thus the maximum slew rate should be less further down the time scale.