An enhanced analytical Neuro-Space Mapping method for large-signal microwave device modeling

Abstract

In this paper, an advanced Neuro-Space Mapping (SM) modeling technique for nonlinear device modeling is proposed. By neural network mapping of the voltage and current signals from the coarse to the fine models, Neuro-SM can modify the behavior of the coarse model to match that of the fine model. The novelty of our work is to introduce a Neuro-SM model combining separate mappings for voltage and current and to derive analytical mapping representation to train the mapping neural networks to learn DC, small and large-signal data. Application examples on modeling MESFET devices and the use of the new model in DC, combined DC,S-parameter and Harmonic balance (HB) simulation demonstrate that our analytical Neuro-SM model matches more closely with the device data than that by the previous Neuro-SM method for modeling large-signal microwave devices.