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Author (up) Morocho-Cayamcela, M.E. & W. Lim
Title Lateral confinement of high-impedance surface-waves through reinforcement learning Type Journal Article
Year 2020 Publication Electronics Letters Abbreviated Journal
Volume Vol. 56 Issue 23, 12 November 2020 Pages pp. 1262-1264
Abstract The authors present a model-free policy-based reinforcement learning

model that introduces perturbations on the pattern of a metasurface.

The objective is to learn a policy that changes the size of the

patches, and therefore the impedance in the sides of an artificially structured

material. The proposed iterative model assigns the highest reward

when the patch sizes allow the transmission along a constrained path

and penalties when the patch sizes make the surface wave radiate to

the sides of the metamaterial. After convergence, the proposed

model learns an optimal patch pattern that achieves lateral confinement

along the metasurface. Simulation results show that the proposed

learned-pattern can effectively guide the electromagnetic wave

through a metasurface, maintaining its instantaneous eigenstate when

the homogeneity is perturbed. Moreover, the pattern learned to

prevent reflections by changing the patch sizes adiabatically. The

reflection coefficient S1, 2 shows that most of the power gets transferred

from the source to the destination with the proposed design.
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
Area Expedition Conference
Notes Approved no
Call Number cidis @ cidis @ Serial 139
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