Convolutional Neural Network for Coupling Matrix Extraction of Microwave Filters

Authors

  • Tarek Sallam 1) School of Applied Technology, Qujing Normal University, Qujing, Yunnan, PR China 655011 2) Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt
  • Ahmed M. Attiya Microwave Engineering Dept., Electronics Research Institute (ERI), Cairo, Egypt

DOI:

https://doi.org/10.13052/2022.ACES.J.370707

Keywords:

Convolutional neural network, coupling matrix, deep learning, microwave filters, parameters extraction

Abstract

Tuning a microwave filter is a challenging problem due to its complexity. Extracting coupling matrix from given S-parameters is essential for ?lter tuning and design. In this paper, a deep-learning-based neural network namely, a convolutional neural network (CNN) is proposed to extract coupling matrix from S-parameters of microwave filters. The training of the proposed CNN is based on a circuit model. In order to exhibit the robustness of the new technique, it is applied on 5- and 8-pole filters and compared with a shallow neural network namely, radial basis function neural network (RBFNN). The results reveal that the CNN can extract the coupling matrix of target S-parameters with high accuracy and speed.

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Author Biographies

Tarek Sallam, 1) School of Applied Technology, Qujing Normal University, Qujing, Yunnan, PR China 655011 2) Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt

Tarek Sallam was born in Cairo, Egypt, in 1982. He received the B.S. degree in electronics and telecommunications engineering and the M.S. degree in engineering mathematics from Benha University, Cairo, Egypt, in 2004 and 2011, respectively, and the Ph.D. degree in electronics and communications engineering from Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt, in 2015. In 2006, he joined the Faculty of Engineering at Shoubra, Benha University. In 2019, he joined the Faculty of Electronic and Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, China. In 2022, he joined the School of Applied Technology, Qujing Normal University, Qujing, Yunnan, China, where he is currently an Associate Professor. He was a Visiting Researcher with the Electromagnetic Compatibility Lab, Osaka University, Osaka, Japan, from August 2014 to May 2015. His research interests include evolutionary optimization, neural networks and deep learning, phased array antennas with array signal processing and adaptivebeamforming.

Ahmed M. Attiya, Microwave Engineering Dept., Electronics Research Institute (ERI), Cairo, Egypt

Ahmed M. Attiya received the M.Sc. and Ph.D. degrees in electronics and electrical communications from the Faculty of Engineering, Cairo University, Cairo, Egypt, in 1996 and 2001, respectively. He joined the Electronics Research Institute as a Researcher Assistant in 1991. In the period from 2002 to 2004, he was a Postdoc with the Bradley Department of Electrical and Computer Engineering, Virginia Tech. In the period from 2004 to 2005, he was a Visiting Scholar with Electrical Engineering Department, University of Mississippi. In the period from 2008 to 2012, he was a Visiting Teaching Member with King Saud University. He is currently a Full Professor and the Head of Microwave Engineering Department, Electronics Research Institute. He is also the Founder of Nanotechnology Lab., Electronics Research Institute.

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Published

2022-12-29

How to Cite

[1]
T. . Sallam and A. M. . Attiya, “Convolutional Neural Network for Coupling Matrix Extraction of Microwave Filters”, ACES Journal, vol. 37, no. 07, pp. 805–810, Dec. 2022.