An architecture design using VLSI building blocks for dynamic programming neural networks

Abstract

An architecture for dynamic programming neural networks is presented. The architecture is based on a building block paradigm in which the network is constructed from neuron array and weight assignment chips. Because of its simple and regular structure, the architecture is a feasible implementation for dynamic programming neural networks with current VLSI technology. Moreover, this architecture can be further extended to other Hopfield-Tank type networks.<>