Journal
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
Volume 66, Issue 7, Pages 3718-3723Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAP.2018.2823775
Keywords
Artificial neural network (ANN); data classification; Fabry-Perot (FP) resonator antenna; performance parameters
Funding
- National Natural Science Foundation of China [61471105, 61331007]
- 973 Project [613273]
Ask authors/readers for more resources
In this communication, a novel artificial neural network (ANN) model is proposed to describe the antenna performance with various parameters. In this model, three parallel and independent branches are involved for three different performance parameters. Meanwhile, a data-classification technique of support vector machine is also included to classify geometrical variables into the proper categories. Once the geometrical variables are input, the ANN model can simultaneously obtain S-parameter, gain, and radiation pattern from the independent branches. The validity and efficiency of this proposed model are confirmed with a Fabry-Perot resonator antenna example.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available