An application of Verilog-A to modeling of back propagation algorithm in neural networks

Abstract

This paper describes an application of the Verilog-A, which is a hardware description language for analog applications, to the modeling of neural networks. We attempt to simulate neural networks having a learning algorithm, which has not been designed with electronic circuits. The learning algorithm is modeled with Verilog-A and the suitable synaptic weights are solved by Verilog-A simulation.