Artificial Neural Network Nonlinear Transistor Behavioral Models: Structure and Parameter Determination Process Based on the Cardiff Model

This article introduces a novel Artificial Neural Network (ANN) structure magentadetermination process, based on the Cardiff Model (CM), to determine ANN-based transistor non-linear behavioral models.By relating the CM formulation and coefficients to the Taylor series expansion of the ANN model, a novel approach for determining the required values of a Fully Connected Cascaded (FCC) ANN structure has been formulated.The proposed method provides the chance to escape from the possible time-consuming ANN magentadetermination process.Experiments proved that the proposed ANN models using the magentadetermination method can provide accurate prediction for the behavior acquired from load-pull characterizations of a Wolfspeed 10 W packaged gallium nitride (GaN) High Electron Mobility Transistor (HEMT) simulation at 3.5 GHz, and a dense load-pull measurement of WIN NP12 4x75 um GaN HEMT at 20 GHz, with Normalized Mean Square Error (NMSE) levels lower than -40 dB.