Power-Ground Plane Impedance Modeling Using Deep Neural Networks and an Adaptive Sampling Process

• Autorzy: Goay Chan Hong , Cheong Zheng Quan , Low Chen En , Ahmad Nur Syazreen , Goh Patrick

Identyfikatory

DOI

10.24425/ijet.2022.143887

• Języki publikacji: EN

Abstrakty

EN

This paper proposes a deep neural network (DNN) based method for the purpose of power-ground plane impedance modeling. A composite DNN model, which is a combination of two DNNs is used to predict the Z-parameters of power ground planes from their design parameters. The first DNN predicts the normalized Z-parameters whereas the second DNN predicts the original maximum and minimum values of the nonnormalized Z-parameters. This allows the method to retain a high accuracy when predicting responses that have large variations across designs, as is the case with the Z-parameters of the power-ground planes. We use the adaptive sampling algorithm to generate the training and validation samples for the DNNs. The adaptive sampling algorithm starts with only a few samples, then slowly generates more samples in the non-linear regions within the design parameters space. The level of non-linearity of the regions is determined by a surrogate model which is also trained using the generated samples as well. If the surrogate model has poor prediction accuracy in a region, then the adaptive sampling algorithm will generate more samples in that region. A shallow neural network is used as the surrogate model for non-linearity determination of the regions since it is faster to train and update. Once all the samples have been generated, they will be used to train and validate the composite DNN models. Finally, we present two examples, a square-shaped power ground plane and a squareshaped power ground plane with a hollow square at the center to demonstrate the robustness of the DNN composite models.

Słowa kluczowe

EN

adaptive sampling; deep neural network; deep learning; power-ground plane; Z-parameters

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2022
• Tom: Vol. 68. No. 4
• Strony: 793--798
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wykr.

Twórcy

autor

Goay Chan Hong

• School of Electrical and Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia

autor

Cheong Zheng Quan

• chool of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

autor

Low Chen En

• emulus Corporation, 11900 Bayan Lepas, Pulau Pinang, Malaysia

autor

Ahmad Nur Syazreen

• School of Electrical and Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia

autor

Goh Patrick

• School of Electrical and Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Pulau Pinang, Malaysia

Bibliografia

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Uwagi

1. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

2. This work was supported by the Ministry of Higher Education, Malaysia, through the Fundamental Research Grant Scheme (FRGS) under Grant FRGS/1/2020/TK0/USM/02/7.