Machine Learning for Circuit Aging Simulation

Abstract

The widespread availability of high-quality open source software for behavioral model optimization motivates the investigation of a behavioral approach to the modeling of aged circuits. A continuous-time formulation of a recurrent neural network (RNN) is compatible with transient circuit simulation, and this work evaluates RNN applicability to the modeling of aged circuits. For any reasonable input, the model should be required to produce an output response that is physically plausible. Approaches to imposing physical constraints on black-box models are outlined briefly.