Prospect of Dynamic Metasurface Array Antenna System With Machine Learning

Author:

Kumar Rupesh1

Affiliation:

1. SRM University, India

Abstract

This chapter presents the machine learning (ML) concept for standard RF component design in microwave frequency. It will explain the use of the deep machine learning concept for antenna and other RF components, such as RF filter, and all relevant analysis will be based on the CST simulations. The comparative study of the ML approach and the antenna design tool (such as CST) will be presented in the form of their performance. This chapter will explain the perspectives of ML in RF system design and analysis. This chapter will present the design of the antenna and filter as examples. The simulated results will be obtained by the CST MW Studio and the ML will be implemented in MATLAB.

Publisher

IGI Global

Reference15 articles.

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3. Systematic Design of a Holographic-Based Metasurface Reflector in the Sub-6 GHz Band

4. AESA Adaptive Beamforming Using Deep Learning;S.Bianco;Proceedings of 2020 IEEE Radar Conference,2020

5. Design and Analysis of Programmable Cross-Polarization Converter In Terahertz Band Using Photo-excited Split-ring Resonator Based Metasurface

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