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2023-02-16
Modeling and Optimization of CPW-Fed E-Textile Antenna Using Machine Learning Algorithms
By
Progress In Electromagnetics Research C, Vol. 130, 31-42, 2023
Abstract
In this paper, an electronic textile (E-textile) antenna design using machine learning (ML) algorithms such as polynomial regression, k-nearest neighbor (kNN), random forest regression, and deep neural network (DNN) is proposed for achieving the optimized solution. These ML techniques, including DNN, have been implemented on a python framework and support in selecting efficient optimum design parameters for a co-planar waveguide fed textile antenna to attain the maximum impedance bandwidth performance in 3-24 GHz band, respectively. Moreover, the accuracy of the predicted response values obtained by these ML methods has also been validated by verifying with the CST simulation software tool.
Citation
Arpan H. Shah, Kalyanbrata Ghosh, and Piyush N. Patel, "Modeling and Optimization of CPW-Fed E-Textile Antenna Using Machine Learning Algorithms," Progress In Electromagnetics Research C, Vol. 130, 31-42, 2023.
doi:10.2528/PIERC22122505
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