  We propose that chaotic Glass networks (a class of piecewise-linear Ordinary
Differential Equations) are good candidates for the design of true random
number generators. A Glass network design has the advantage of involving only
standard Boolean logic gates. Furthermore, an already chaotic (deterministic)
system combined with random ``jitter'' due to thermal noise can be used to
generate random bit sequences in a more robust way than noisy limit-cycle
oscillators. Since the goal is to generate bit sequences with as large a
positive entropy as possible, it is desirable to have a theoretical method to
assess the irregularity of a large class of networks. We develop a procedure
here to calculate good upper bounds on the entropy of a Glass network, by means
of symbolic representations of the continuous dynamics. Our method improves on
a result by Farcot (2006), and allows in principle for an arbitrary level of
precision by refinements of the estimate, and we show that in the limiting
case, these estimates converge to the true entropy of the symbolic system
corresponding to the continuous dynamics. As a check on the method, we
demonstrate for an example network that our upper bound after only a few
refinement steps is very close to the entropy estimated from a long numerical
simulation.
