I had to drop the other thread because my message was 43k instead of 40k. Shouldn't we raise that limit? I don't even know if there's actually someone moderating those emails. -------------------------
Hi, Julius and Oleg. > The question remains as to which filter form is more accurate. > > Another thing worth mentioning, by the way, is that tf2snp can be > modulated, even using white noise for its coefficients, without affecting > signal energy. > That's the usual and original principal benefit of going to the normalized > ladder form - "power-invariant modulatability". > The superior numerical robustness for closely spaced poles was observed > later and documented in the literature by Gray and Markel, as I recall. > > - Julius > Below we have a simple test to see how much the filters diverge from the expected 1/sqrt(2) attenuation at cut-off. The filters are tested with 12 frequencies, the first 12 octaves starting at ~15.85 Hz. The values show the attenuation error in dBs. I'm calculating the RMS with an.rms_envelope_tau(10) for a steady RMS calculation and I'm taking the values after a thousand seconds to be sure that the RMS filters are fully charged. I did the test at 96kHz SR, double precision. We have: highpass(2), snp, svf_oleg, svf_zava. At least for the audible spectrum, they all seem to perform pretty well. Hard to tell which one is best for the time-invariant case, isn't it? Ciao, Dario 15.8489323, 0.0035875327635620513, 0.0035875324371487105, 0.0035875327635620513, 0.0035875327636175625, 31.622776, 0.0013189248524392294, 0.0013189248481326743, 0.0013189248529810182, 0.0013189248528688857, 63.0957336, -0.00014836658605854591, -0.00014836659250561102, -0.00014836658607297881, -0.00014836658600858588, 125.89254, -0.00029188057887152841, -0.00029188057380447052, -0.00029188057895590536, -0.00029188057892148844, 251.188644, 0.00010734229401176965, 0.00010734229400843898, 0.00010734229401621054, 0.00010734229399067541, 501.187225, -0.0001285532826483804, -0.00012855328314131942, -0.00012855328263283727, -0.00012855328265393151, 1000, -2.7386120134975656e-05, -2.7386120134975656e-05, -2.7386120134975656e-05, -2.7386120134975656e-05, 1995.26233, 5.9325435514123726e-06, 5.9325435203261279e-06, 5.9325435536328186e-06, 5.9325435569634877e-06, 3981.07178, 1.4404616551222382e-05, 1.4404616547891713e-05, 1.4404616545671267e-05, 1.4404616547891713e-05, 7943.28223, -1.0056763050103612e-06, -1.0056763061205842e-06, -1.0056763072308073e-06, -1.0056763061205842e-06, 15848.9316, -1.1356025741982023e-05, -1.1356025744202469e-05, -1.13560257408718e-05, -1.1356025743092246e-05, 31622.7773 nan, 173.00064800561148, nan, nan -- Dr Dario Sanfilippo http://dariosanfilippo.com
test_hps_acc.dsp
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