Rational interpolation scheme based on Bayesian classifiers for multi-resonance response of radio frequency devices

Formal design optimisation techniques are commonly used for designing new radio frequency devices. The search for globally optimum designs turns out to be exhaustive primarily since full-wave electromagnetic (EM) simulation tools used in the repetitive analysis process during the design cycle consume plenty of time and resources. In this study, a new technique is introduced in order to reduce the number of analysis calls in a frequency-dependent EM optimisation cycle by providing a robust interpolation of the EM frequency response. The proposed technique makes use of Bayes' theorem incorporated with both rational interpolations and an adaptive sampling technique. The technique is tested on approximating the return loss curves of ten design candidates of a microstrip patch antenna. Results are compared with linear interpolation scheme demonstrating the technique's capability of accurately predicting poles and approximating resonance-based behaviour such as bandwidth with improved accuracy.