Bioinspired multiobjective synthesis of X‐band FSS via general regression neural network and cuckoo search algorithm

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Abstract
A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015
Funding Information
  • CNPq (573939/2008-0 (INCT-CSF))

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