| 摘要 |
A system for estimating bit error rates (BER) may include using a normalization factor that scales a BER to substantially normalize a Q-scale for a distribution under analysis. A normalization factor may be selected, for example, to provide a best linear fit for both right and left sides of a cumulative distribution function (CDF). In some examples, the normalized Q-scale algorithm may identify means and probabilistic amplitude(s) of Gaussian jitter contributors in the dominant extreme behavior on both sides of the distribution. For such contributors, means may be obtained from intercepts of both sides of the CDF(Qnorm(BER) with the Q(BER)=0 axis, standard deviations (sigmas) may be obtained from reciprocals of slopes of best linear fits, and amplitudes may be obtained directly from the normalization factors. In an illustrative example, a normalized Q-scale algorithm may be used to accurately predict bit error rates for sampled repeating or non-repeating data patterns.
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