ANN Modelling of Planar Filters Using Square Open Loop DGS Resonators

Nedelchev, Marin; Marinković, Zlatica; Kolev, Alexander

doi:10.1007/978-3-030-23976-3_32

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…Moreover, the ANN based approach has been applied to perform inverse modeling of the filter. Namely, the ANNs are used to determine the distance between the filter resonators for the given coupling properties [7]- [8] or resonator dimensions and the given coupling coefficient [5]- [6]. However, the developed models of the filter coupling properties shown in [5] are valid for only one considered dielectric material (i.e., for one specified value of the relative dielectric constant).…”

Section: Introductionmentioning

confidence: 99%

Prior knowledge based neural modeling of microstrip coupled resonator filters

et al. 2022

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The design of microstrip coupled resonator filters includes determination of the coupling coefficients between the filter resonator units. In this paper a novel modeling procedure exploiting prior knowledge neural approach is proposed as an efficient alternative to the standard electromagnetic (EM) simulations and to the neural models based purely on the artificial neural networks (ANNs). It has similar accuracy as the EM simulations and requires less training data and less time needed for the model development than the models based purely on ANNs.

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