Mode Recognition of Rectangular Dielectric Resonator Antenna Using Artificial Neural Network
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 5209-5216 |
| Journal / Publication | IEEE Transactions on Antennas and Propagation |
| Volume | 70 |
| Issue number | 7 |
| Online published | 2 Feb 2022 |
| Publication status | Published - Jul 2022 |
Link(s)
Abstract
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.
Research Area(s)
- Antenna measurements, artificial intelligence, artificial neural network, Artificial neural networks, Dielectric resonator antenna, Dielectric resonator antennas, mode recognition, Neurons, Optical resonators, particle swarm optimization, Resonant frequency, resonant mode, Training
Citation Format(s)
Mode Recognition of Rectangular Dielectric Resonator Antenna Using Artificial Neural Network. / Xiao, Yuqi; Leung, Kwok Wa; Lu, Kai et al.
In: IEEE Transactions on Antennas and Propagation, Vol. 70, No. 7, 07.2022, p. 5209-5216.
In: IEEE Transactions on Antennas and Propagation, Vol. 70, No. 7, 07.2022, p. 5209-5216.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
