| Fixed-Point Toolbox™ | ![]() |
[f,x] = errpdf(q)
f = errpdf(q,x)
[f,x] = errpdf(q) returns the probability density function f evaluated at the values in x. The vector x contains the uniformly distributed random quantization errors that arise from quantizing a signal by quantizer object q.
f = errpdf(q,x) returns the probability density function f evaluated at the values in vector x.
Note The results are not exact when the signal precision is close to the precision of the quantizer. |
q = quantizer('nearest',[4 3]);
[f,x] = errpdf(q);
subplot(211)
plot(x,f)
title('Computed PDF of the quantization error.')
The output plot shows the probability density function of the quantization error.

Compare this result to a plot of the sample probability density function from a Monte Carlo experiment:
r = realmax(q);
u = 2*r*rand(10000,1)-r; % Original signal
y = quantize(q,u); % Quantized signal
e = y - u; % Error
subplot(212)
hist(e,20);set(gca,'xlim',[min(x) max(x)])
title('Estimate of the PDF of the quantization error.')

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