ScholarMate
客服热线:400-1616-289

Mode Recognition of Rectangular Dielectric Resonator Antenna Using Artificial Neural Network

Xiao, Yuqi; Leung, Kwok Wa; Lu, Kai*; Leung, Chi-Sing
Science Citation Index Expanded
中山大学

摘要

A new method powered by an artificial neural network (ANN) is studied for resonant-mode recognitions of a rectangular dielectric resonator antenna (DRA). Different rectangular DRAs were simulated with ANSYS HFSS to generate a large dataset for training the model. Their resonance frequencies, dimensions, and 3-D electric fields are input to the ANN. The output end is a 12-element array representing the corresponding probabilities of 12 different resonant modes. Using this trained ANN model, the mode recognition accuracy can reach 96.74%. Apart from identifying the resonant modes, our proposed approach can suggest how to modify a rectangular DRA to improve the purity of a resonant mode for better antenna performance.

关键词

Artificial neural networks Neurons Training Antenna measurements Resonant frequency Dielectric resonator antennas Optical resonators Artificial intelligence (AI) artificial neural network (ANN) dielectric resonator antenna (DRA) mode recognition particle swarm optimization (PSO) resonant mode