Hyper-parameter optimized GPR model based on chaos game algorithm for RF power transistors

In this paper, a new frequency domain behavior model for radio frequency (RF) power transistors based on a hyper-parameter optimized Gaussian process regression (GPR) method is presented. The chaos game optimization (CGO) algorithm is used to optimize GPR hyperparameters, resulting in the CGO-GPR model. The basic theory as well as the details of the modeling process are presented. Validation of the model is conducted using a 10-watt GaN power transistor. Compared to the standard GPR model, the proposed model achieved a significant improvement. Furthermore, the comparison with the particle swarm optimization (PSO) based GPR model (PSO-GPR) showed that the proposed model allows achieving superior performance, thereby confirming the effectiveness of the developed modeling technique.