  One of the fundamental problems of information theory, since its foundation
by Shannon in 1948, has been the computation of the capacity of a discrete
memoryless channel, a quantity expressing the maximum rate at which information
can travel through the channel. In the literature, several algorithms were
proposed to approximately compute the capacity of a discrete memoryless
channel, being an analytical solution unavailable for the general discrete
memoryless channel. This paper presents a novel approach to compute the
capacity, which is based on a continuous-time dynamical system. Such a
dynamical system can indeed be regarded as a continuous-time version of the
Blahut-Arimoto algorithm. In fact, the updating map appearing in the
Blahut-Arimoto algorithm is here obtained as a suitable discretization of the
vector flow presented, using an analogy with some game-theoretical models.
Finally, this analogy suggests a high-level hardware circuit design enabling
analog computation to estimate the capacity.
