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Measured Amplitude Response

Figure 8.3 shows a plot of simulated amplitude-response measurements at 10 frequencies equally spread out between 100 Hz and 3 kHz on a log frequency scale. The ``measurements'' are indicated by circles. Each circle plots, for example, the output amplitude divided by the input amplitude for a sinusoidal input signal at that frequency [452]. These ten data points are then extended to dc and half the sampling rate, interpolated, and resampled to a uniform frequency grid (solid line in Fig.8.3), as needed for FFT processing. The details of these computations are listed in Fig.8.4. We will fit a four-pole, one-zero, digital-filter frequency-response to these data.9.14

Figure 8.3: Example measured amplitude-response samples at 10 exponentially spaced frequencies. Circles: Measured amplitude-response points. Solid: Extrapolated, spline-interpolated, and uniformly resampled amplitude response, ready for ifft.
\includegraphics[width=\twidth]{eps/tmps2-G}

Figure: Script (matlab) for simulating a measured amplitude response at 10 exponentially spaced frequencies and extrapolating/interpolating/resampling to obtain a complete, nonparametric amplitude response, uniformly sampled at FFT frequencies. This script generated Fig.8.3.

 
NZ = 1;      % number of ZEROS in the filter to be designed
NP = 4;      % number of POLES in the filter to be designed
NG = 10;     % number of gain measurements
fmin = 100;  % lowest measurement frequency (Hz)
fmax = 3000; % highest measurement frequency (Hz)
fs = 10000;  % discrete-time sampling rate
Nfft = 512;  % FFT size to use 
df = (fmax/fmin)^(1/(NG-1)); % uniform log-freq spacing
f = fmin * df .^ (0:NG-1);   % measurement frequency axis

% Gain measurements (synthetic example = triangular amp response):
Gdb = 10*[1:NG/2,NG/2:-1:1]/(NG/2); % between 0 and 10 dB gain

% Must decide on a dc value.
% Either use what is known to be true or pick something "maximally
% smooth".  Here we do a simple linear extrapolation:
dc_amp = Gdb(1) - f(1)*(Gdb(2)-Gdb(1))/(f(2)-f(1));

% Must also decide on a value at half the sampling rate.
% Use either a realistic estimate or something "maximally smooth".
% Here we do a simple linear extrapolation. While zeroing it
% is appealing, we do not want any zeros on the unit circle here.
Gdb_last_slope = (Gdb(NG) - Gdb(NG-1)) / (f(NG) - f(NG-1));
nyq_amp = Gdb(NG) + Gdb_last_slope * (fs/2 - f(NG));

Gdbe = [dc_amp, Gdb, nyq_amp]; 
fe = [0,f,fs/2];
NGe = NG+2;

% Resample to a uniform frequency grid, as required by ifft.
% We do this by fitting cubic splines evaluated on the fft grid:
Gdbei = spline(fe,Gdbe); % say `help spline'
fk = fs*[0:Nfft/2]/Nfft; % fft frequency grid (nonneg freqs)
Gdbfk = ppval(Gdbei,fk); % Uniformly resampled amp-resp

figure(1);
semilogx(fk(2:end-1),Gdbfk(2:end-1),'-k'); grid('on'); 
axis([fmin/2 fmax*2 -3 11]);
hold('on'); semilogx(f,Gdb,'ok');
xlabel('Frequency (Hz)');   ylabel('Magnitude (dB)');
title(['Measured and Extrapolated/Interpolated/Resampled ',...
       'Amplitude Response']);


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``Physical Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2010, ISBN 978-0-9745607-2-4.
Copyright © 2014-06-11 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
CCRMA