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Musical-Applications-of-Microprocessors-2ed-Chamberlin-H-1987

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SOURCE-SIGNAL ANALYSIS 555<br />

-5°<br />

FH<br />

FREQUENCY<br />

(A)<br />

°lrrt\\<br />

-5 [<br />

.~;::=<br />

FREQUENCY<br />

(8)<br />

..<br />

Fig. 16-7. Overlap between analyzer filters. (A) Insufficient overlap. (8) Excessive<br />

overlap.<br />

in Fig. 16-7A, there will be large frequency gaps that none <strong>of</strong> the filters<br />

respond very strongly to. On the other hand, excessive overlap degrades<br />

frequency resolution. Overlap can be characterized by noting at what attenuation<br />

adjacent amplitude responses cross. A good number for the singlesection<br />

bandpass used here is -6 dB or the 50% voltage response points. The<br />

formula for Q based on a 6-dB bandwidth is: Q = 1. 732Fc/(Fh-FI).<br />

Table 16-1 and Fig. 16-8 show the 30-channel bandpass responses<br />

with overlap at the 6-dB points. What is plotted in Fig. 16-8 is the gain<br />

versus frequency for each filter after it has been normalized for unity gain at<br />

the center frequency. This would seem to be the only reasonable way to<br />

normalize filter gains, but a peculiar thing happens if one feeds white noise<br />

into the analyzer. Some channels, notably the high-frequency wide<br />

bandwidth ones, report a higher amplitude than others even though the<br />

input sound has a flat spectrum!<br />

The uneven response is due to the fact that white noise has constant<br />

power per hertz <strong>of</strong> bandwidth, and the wider bandwidth filters therefore<br />

absorb more power. A typical complex music spectrum would show the<br />

same results. On the other hand, a sound having only a few widely spaced<br />

harmonics would be analyzed correctly! The only way to avoid this dilemma<br />

is to use equal bandwidths for all <strong>of</strong> the filters. If wider bandwidths are<br />

desired at the higher frequencies, two or more bands can be averaged, which<br />

does not create problems. Even though the spectral data are reduced, computation<br />

time soars. The filterbank analyzer, therefore, is best suited for rough<br />

analysis <strong>of</strong> dense (lots <strong>of</strong> frequency components) spectra, in which case the<br />

channel gains are normalized for equal response to white noise.<br />

The low-pass filters following the rectifiers must also be specified. As<br />

was mentioned earlier, their primary job is to smooth ripple from the rectifier<br />

without unduly slowing response to sudden spectrum changes. However,<br />

one must be careful to avoid multisection sharp cut<strong>of</strong>f filters because<br />

their step response includes a lot <strong>of</strong> ringing, which would distort the<br />

analysis. A reasonable compromise is a resonant low-pass with a Q <strong>of</strong> around<br />

0.8. Since the spectrum sample rate is 100 Hz, a cut<strong>of</strong>ffrequency <strong>of</strong>30 Hz or<br />

so is indicated. Acceptable ripple rejection in the lowest band may require a

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