+
Review 1
The author first prove the chaotic behaviour of a family of pseudorandom
number generators (PRNG) introduced in a previous work by the same authors.
These PRNGs are based on iterating continuous functions on a discrete domain.
-The paper first recalls Devaney’s definition of chaos and presents the proof of
+ The paper first recalls Devaney’s definition of chaos and presents the proof of
the main results. Next, the authors study the stopping time, i.e. the time until
-a uniform distribution is reached. Finally, they evaluate the PRNG against the
+a uniform distribut
+ion is reached. Finally, they evaluate the PRNG against the
NIST suite.
Review 1
Another concern is the lack of comparison with other existing methods. Such
a comparison should be provided.
---> JFC
+--> CG
For theses reasons, I do not recommend acceptance of this contribution in
Some concerns must be noted on the practical side. It is unclear how the algorithm improves the randomness properties, as the results of the randomness test suite is not compared to that of the input PRNG. If that had been a perfect RNG, only 8 bits would have been enough to generate 8 bits, in this case we need 582 bits according to Table 1. This difference has to be justified.
---> JFC
+--> JFC (fait)
The removal of the Hamiltonian cycle adds an interesting twist to the N-cube, but the importance of this complication is not emphasized properly.
---> JFC
+--> JFC (fait)
It would be also interesting to see the comparison of the theoretical and simulated bounds on tau.
