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Designing high-performance microstrip quad-band bandpass filters (for multi-service communication systems): a novel method based on artificial neural networks

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Abstract

Recently, high-performance multi-channel microstrip filters are widely demanded by modern multi-service communication systems. Designing these filters with both compact size and low loss is a challenge for the researchers. In this paper and for the first time, we have proposed a novel method based on artificial neural network to design and simulate multichannel microstrip bandpass filters. For this purpose, the frequency, physical dimensions, and substrate parameters, i.e., type and thickness, of the BPF are selected as the inputs and the S-parameters, i.e. S11 and S21, are selected as the outputs of the proposed model. Using an accurate multilayer perceptron neural network trained with back-propagation technique, a high-performance microstrip quad-band bandpass filter (QB-BPF) is designed which has a novel compact structure consisting of meandrous spirals, coupled lines, and patch feeds. The proposed method can be easily used for designing other microstrip devices such as filters, couplers, and diplexers. The designed filter occupies a very small area of 0.0012 λg2, which is the smallest size in comparison with previously published works. It operates at 0.7, 2.2, 3.8, and 5.6 GHz for communication systems. The low insertion loss, high return losses, low group delay, and good frequency selectivity are obtained. To verify the design method and simulation results, the introduced filter is fabricated and measured. The results show an agreement between the simulation and measurement.

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Acknowledgements

Authors would like to acknowledge: the financial support of Kermanshah University of Technology for this research under grant number S/P/T/1177, in part support by Koya University under Grant 03/08/3560, and in part support by Cihan University-Erbil under Grant 68/2019.

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Authors and Affiliations

  1. Department of Electrical Engineering, Kermanshah University of Technology, Kermanshah, Iran

    Abbas Rezaei

  2. Department of Communication and Computer Engineering, Cihan University-Erbil, Erbil, Kurdistan Region, Iraq

    Salah I. Yahya

  3. Department of Software Engineering, Faculty of Engineering, Koya University, KOY45, Koya, Kurdistan Region, Iraq

    Salah I. Yahya

  4. Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran

    Leila Noori

  5. Wireless Communication Centre, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia

    Mohd Haizal Jamaluddin

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  1. Abbas Rezaei
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Rezaei, A., Yahya, S.I., Noori, L. et al. Designing high-performance microstrip quad-band bandpass filters (for multi-service communication systems): a novel method based on artificial neural networks. Neural Comput & Applic 34, 7507–7521 (2022). https://doi.org/10.1007/s00521-021-06879-7

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