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m = errmean(q)
m = errmean(q) returns the mean of a uniformly distributed random quantization error that arises from quantizing a signal by quantizer object q.
Note The results are not exact when the signal precision is close to the precision of the quantizer. |
Find m, the mean of the quantization error for quantizer q:
q = quantizer; m = errmean(q) m = -1.525878906250000e-005
Now compare m to m_est, the sample mean from a Monte Carlo experiment:
r = realmax(q); u = 2*r*rand(1000,1)-r; % Original signal y = quantize(q,u); % Quantized signal e = y - u; % Error m_est = mean(e) % Estimate of the error mean m_est = -1.519507450175317e-005

Learn how to apply early verification to your development process through these technical resources.
How much time do you spend on testing to ensure implementation meets system-level requirements?
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