Bayesian Optimisation of a Frequency Selective Surface Using a Regularised Objective Function - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Bayesian Optimisation of a Frequency Selective Surface Using a Regularised Objective Function

Résumé

This work introduces a penalty-based regularisation to optimise the geometric parameters of a periodic frequency selective surface. The equivalent circuit of a multi-layer bandpass filter is used to illustrate the benefits of the approach for wideband applications. The proposed regularisation is obtained by convolving the frequency response and the desired thresholds before measuring the infraction. We apply bayesian optimisation on the unconstrained optimisation problem and assess the performance of the strategy by the number of objective function evaluations. A faster convergence is observed with the proposed regularisation.
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Dates et versions

hal-03770686 , version 1 (30-09-2022)

Identifiants

Citer

Kilian Bihannic, Jérémy Omer, Renaud Loison, Guillaume Reille. Bayesian Optimisation of a Frequency Selective Surface Using a Regularised Objective Function. 16th European Conference on Antennas and Propagation (EuCAP), Mar 2022, Madrid, Spain. ⟨10.23919/EuCAP53622.2022.9769068⟩. ⟨hal-03770686⟩
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