  In this work we propose a new model of 2D cellular neural networks (CNN) in
terms of the lattice FitzHugh-Nagumo equations with boundary feedback and prove
a threshold condition for the exponential synchronization of the entire neural
network through the \emph{a priori} uniform estimates of solutions and the
analysis of dissipative dynamics. The threshold to be satisfied by the gap
signals between pairwise boundary cells of the network is expressed by the
structural parameters and adjustable. The new result and method of this paper
can also be generalized to 3D and higher dimensional FitzHugh-Nagumo type or
Hindmarsh-Rose type cellular neural networks.
