An Extraction Method Based on Artificial Neural Network Techniques for Novel Cardiff Model With Reasonable Extrapolation Behavior

This letter presents an advanced Cardiff Model (CM) extraction method based on artificial neural network (ANN) techniques that ensures reasonable extrapolation behavior. The nonphysical extrapolation behavior occurring with CMs using a high, user-defined, mixing order, i.e., false output optima point and erroneous efficiency behavior, when extracted using measured load-pull datasets can be avoided with the proposed method. The method proposed maintains the accuracy within the load-pull measurements, design-relevant, impedance space. The method was verified by modeling the measured load-pull data of a Wolfspeed 10-W gallium nitride (GaN) packaged device and a WIN Semiconductors GaN on-wafer device. With both the devices, the extrapolation issues shown when using the high-order CM are removed by the novel extracted CM coefficients.