Banca de QUALIFICAÇÃO: ADELSON MENEZES LIMA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
DISCENTE : ADELSON MENEZES LIMA
DATA : 06/07/2018
HORA: 08:00
LOCAL: Auditório do PPGEEC
TÍTULO:

An Approach Based on Reinforcement Learning  for Microstrip Antenna Design

PALAVRAS-CHAVES:

Reinforcement Learning; Q-learning; Microstrip Antennas; Return Loss; Inset-fed.

PÁGINAS: 50
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
SUBÁREA: Telecomunicações
ESPECIALIDADE: Teoria Eletromagnetica, Microondas, Propagação de Ondas, Antenas
RESUMO:

The growing demand for wireless communication for data, video and voice has become an attractive feature in the use of microstrip antennas built into portable devices, imposing more demanding antenna designs to meet the requirements of accuracy and performance. However, a careful analysis in obtaining the design parameters of antennas is essential to guarantee a proper functioning of the structure. In this context, the machine learning technique called Reinforcement Learning (RL), through the Q-learning algorithm, is applied in microstrip antennas to obtain parameters in projects. It was initially applied to the problem of impedance matching between the power line and the radiant element of a rectangular microstrip antenna, in order to determine the best value of inset-fed (y₀) in the radiant element (patch). Finally, the efficacy of RL is achieved and proven through the fabrication of prototypes of the structures, followed by results measured in a specialized laboratory and compared to the simulated results.

MEMBROS DA BANCA:
Presidente - 1422265 - JOSE PATROCINIO DA SILVA
Interno - 1412682 - VICENTE ANGELO DE SOUSA JUNIOR
Externo à Instituição - HUMBERTO DIONISIO DE ANDRADE - UFERSA