Neural networks for switching

Abstract

The author argues that a strong impetus for using neural networks is that they provide a framework for designing massively parallel machines. He notes that the highly interconnected architecture of switching networks suggests similarities to neural networks. He presents two switching applications in which neural networks can solve the problems efficiently. He shows that a computational advantage can be gained by using nonuniform time delays in the network.