Neural Networks for Switching

Brown, T.X

IEEE Communications Magazine, Vol. 27, No. 11, pp. 72--81, 1989

Abstract:
Neural networks are a class of systems that have many simple
processors---neurons---which are highly interconnected. The function of
each neuron is simple, and the behavior is determined predominately by
the set of interconnections. Thus, a neural network is a special form of
a parallel computer. Although a major impetus for using neural networks
is that they may be able to ``learn'' the solution to the problem that
they are to solve, we argue that another, perhaps even stronger, impetus
is that they provide a framework for designing massively parallel
machines. The highly interconnected architecture of switching networks
suggests similarities to neural networks. here, we present two switching
applications in which neural networks can solve the problems efficiently.
We also show that a computational advantage can be gained by using
nonuniform time delays in the network.