This chapter deals with the use of the Statistical Complexity Measure, as defined by
Lopez Ruiz, Mancini and Calbet [Phys. Lett. A 209 (1995) 321–326] and modified by
Rosso and coworkers [P. W. Lamberti, M. T. Martin, A. Plastino, O. A. Rosso; Physica
A 334 (2004) 119–131] to characterize pseudo random number generators (PRNG’s)
obtained from chaotic dynamical systems. It is shown that two probability distribution
functions are required for a proper characterization: the first one is based on the
histogram and is used to characterize the uniformity of the values in the time series;
the second one is based on the permutation procedure proposed by Bandt and Pompe
[Phys. Rev. Lett. 88 (2002) 174102] and characterize the uniformity of patterns of
several consecutive values of the time series.
Keywords: Chaos, Random number generators, Entropy, Statistical Complexity.
