A Novel Data-Driven Analysis Method For Nonlinear Electromagnetic Radiations Based On Dynamic Mode Decomposition

Abstract

Nonlinear effects generated in complex electronic systems such as cell phones and computers cause broadband electromagnetic radiations. They are very difficult to model but could be key contributors to the radiated spurious emission (RSE) and radio frequency interference (RFI). In this paper, a novel data-driven characterization method is proposed to analyze the transient responses of the nonlinear circuits and their nonlinear electromagnetic radiations. It employs the dynamic mode decomposition (DMD) to simultaneously extract the temporal patterns and their corresponding dynamic modes. The temporal patterns show high order harmonics generated by the nonlinearity. Then these temporal spatial coherent patterns could provide physical insight of the radiation and fast predictions of future states in nonlinear circuit and electromagnetic systems. Nonlinear benchmarks are provided to demonstrate the validity of the proposed new analysis method. According to our best knowledge, this is the first time RSE and RFI are characterized by DMD, a data-driven method purely based on measured or simulated data.