Appendix F: Miscellaneous
Random (rnd) Function
F 6
A random number generation algorithm uses an uniform distribution random
generation routine and the central-limit theorem to derive Gaussian distribution
random numbers.
Central-limit theorem: when the independent random variables X
conform to an identical random distribution, the mean and variance of x = (X
X
+... + X
)/n are given as follows:
2
n
E(n) + m
Even if the initial random distribution is not normal, if a reasonably large value
for n is used, the arithmetical mean x of a considerably large number of variables
will be close to the normal distribution.
In actuality, 12 is used for n, uniform random numbers are accumulated n times
and their arithmetical mean is derived as the ultimate Gaussian distribution
random number.
The following algorithm is used to generate uniform distribution random
numbers:
seed [n] + (253.0
seed [n–1] ) 1.0) mod 16777216
ran + seed [n] 16777216
V(n) + s
n
2
, X
..., and X
1
2
n
+
1
AWG2021 User Manual
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