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FSS Derived Using a New Equivalent Circuit Model Backed Deep Neural Network

Varun Chaudhary, Ravi Panwar

2021IEEE Antennas and Wireless Propagation Letters30 citationsDOI

Abstract

An equivalent circuit model backed deep neural network (DNN) is introduced to develop a broadband frequency selective surface (FSS). Shielding effectiveness (SE) and resonant frequency are inputs and shielding structure parameters are the outputs of the DNN. Moreover, three different configurations of DNN are investigated to get a minimum mean square error of 2.99 × <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10^{-6}$</tex-math></inline-formula> between targeted and observed outputs. The size of FSS is 0.30 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lambda _0$</tex-math></inline-formula> × 0.30 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lambda _0$</tex-math></inline-formula> and the total thickness of the shielding structure is only 0.1 mm. The variation in resonance frequency is only 0.08 GHz when the angle of incidence changes from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\theta$</tex-math></inline-formula> = <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0^\circ$</tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{80}^\circ$</tex-math></inline-formula> for transverse electric polarization. Furthermore, a fractional bandwidth of 80 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\%}$</tex-math></inline-formula> is achieved with a resonance at 10 GHz. The broad shielding bandwidth, ultrathin, polarization-insensitivity, wide angular stability attained by using a new, very simple, and miniaturized geometry are a few key features of the proposed structure. The results obtained from DNN are validated using full-wave simulation and by measurement of the fabricated prototype. SE performance concurs well among all demonstrate the effectiveness of the aforementioned technique for electromagnetic interference shielding application.

Topics & Concepts

NotationArtificial neural networkMathematicsAlgorithmLambdaArtificial intelligenceComputer scienceArithmeticPhysicsOpticsAdvanced Antenna and Metasurface TechnologiesMetamaterials and Metasurfaces ApplicationsAntenna Design and Analysis