A Generative Method for Antenna Optimization

The key to rapid antenna design is to improve the optimization of design parameters by simplifying the modeling of antenna geometric structures. We propose a flexible geometric modeling scheme that can be formed into any arbitrary shape by simply connecting nodes. We also propose a machine learning based generative method for high dimensional design parameter problems. It consists of discriminators and generators. The discriminators predict the performance of geometric models and the generators create new candidates that will pass the discrim-inators. Further, an evolutionary criterion approach is applied to update the discriminators and generators. The efficiency of the new design methodology is illustrated by a dual resonance antenna design example.