  This paper discusses and analyzes various models of binary correlated
sources, which may be relevant in several distributed communication scenarios.
These models are statistically characterized in terms of joint Probability Mass
Function (PMF) and covariance. Closed-form expressions for the joint entropy of
the sources are also presented. The asymptotic entropy rate for very large
number of sources is shown to converge to a common limit for all the considered
models. This fact generalizes recent results on the information-theoretic
performance limit of communication schemes which exploit the correlation among
sources at the receiver.
