The generator only generates bit 1 when the value of its bit counter is equal to M j.
There are applications, which, without loss of generality, generate bit-streams, associated to different users.
Assume that the generated bit stream is of length.
ROPUF exploits comparisons of measured frequencies, obtained by picking a RO pair, aiming to generate bit responses.
Long randomly generated bit strings, no matter how they were obtained, are algorithmically complex but need not have any relationship to chaos.
If a demon performed a large number of cycles without erasing its memory, as Penrose suggested, then its memory would contain a randomly generated bit string.
However, long randomly generated bit strings are, with high probability, incompressible, so unless the demon was very lucky, this could not work.
Therefore, we would like to modify these random bit generating protocols, such that the generated bit vector does not change when for a new execution the same users happen to be online.
At 1.25 GHz sampling rate, a significant number of the sampling measurements occur between large peaks, resulting in degraded randomness of the generated bit sequence.
To provide a suitable example, we consider a coded system with phase noise described in scenario 2, with a 128-QAM constellation and a randomly generated bit labeling.
Then, in order to increase the output throughput and the statistical quality of the generated bit sequences, we propose a TRNG design which uses a dual oscillator architecture with the proposed continuous-time chaotic oscillator.
