Statistical Complexity of Chaotic Pseudorandom Number Generators
Pp. 283-308 (26)
Hilda A. Larrondo, Luciana De Micco, Claudio M. Gonzalez, Angelo Plastino and Osvaldo A. Rosso
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.
Chaos, Random number generators, Entropy, Statistical Complexity.
Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, 7600 Mar del Plata, Argentina