An efficient technique for modeling radar cross section magnitude responses versus frequency is presented. The technique is based on Gaussian process regression and makes it possible to significantly reduce the number of ...

Gaussian process (GP) regression is proposed as a structured supervised learning alternative to neural networks for the modeling of CPW-fed slot antenna input characteristics. A Gaussian process is a stochastic process ...

A two-stage approach based on Gaussian process regression that achieves significantly reduced requirements for computationally expensive high-fidelity training data is presented for the modeling of planar antenna input ...