Verilog-A compatible recurrent neural network model for transient circuit simulation

摘要

This paper presents a method for data-driven behavioral modeling of electronic circuits using recurrent neural networks (RNNs). The RNN structure is adapted based on known characteristics of the system being modeled. The discrete-time RNN is transformed to a continuous-time model and then implemented in Verilog-A for compatibility with general-purpose circuit simulators.