A compact ultrawide bandpass filter along notch characteristics with rectangular resonator through a machine learning approach

Abstract This article presents an ultrawide bandpass filter structure developed along a notch band using a small rectangular impedance resonator. The proposed filter structure consists of a coupled rectangular resonator (CRR), open stub, and composited split ring resonator (CSRR) at the bottom of the structure. In-band and out-of-band properties are improved by the CRR and open stub. The notch band is obtained by placing CSRR below the rectangular resonator. A filter with a compact size of 0.15 × 0.10 λg is obtained at a lowered cutoff frequency of 3.0 GHz, where λg is the corresponding guided wavelength. The proposed structure has been constructed on 5880 Rogers substrate with a thickness of 0.787 mm and a dielectric constant of 2.2. Additionally, equivalent lumped parameters were obtained, and a lumped equivalent circuit was created to explain how the suggested filter operated. The Electromagnetic (EM)-simulated results are in good agreement with the circuit-simulated and measured result. The various machine learning approaches such as artificial neural network, K-nearest neighbour, decision tree, random forest (RF), and extreme gradient boosting algorithms are applied to optimize the design, in which RF algorithms achieve more than 90% accuracy for predicting the S parameters of the ultrawideband filter.

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Publication Details

Journal
International Journal of Microwave and Wireless Technologies
Published
2024-10-01
DOI
https://doi.org/10.1017/s1759078725000029
Citations
3
Primary Topic
Microwave Engineering and Waveguides
Type
article
Field-Weighted Citation Impact
0.63
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article

A compact ultrawide bandpass filter along notch characteristics with rectangular resonator through a machine learning approach

Dilip Kumar Choudhary, Pinku Ranjan, Rakesh Chowdhury, Jayant Kumar
3 citations
International Journal of Microwave and Wireless Technologies
Microwave Engineering and Waveguides
0.63
article

A compact ultrawide bandpass filter along notch characteristics with rectangular resonator through a machine learning approach

Dilip Kumar Choudhary, Pinku Ranjan, Rakesh Chowdhury, Jayant Kumar
article en
3 citations

Abstract

Abstract This article presents an ultrawide bandpass filter structure developed along a notch band using a small rectangular impedance resonator. The proposed filter structure consists of a coupled rectangular resonator (CRR), open stub, and composited split ring resonator (CSRR) at the bottom of the structure. In-band and out-of-band properties are improved by the CRR and open stub. The notch band is obtained by placing CSRR below the rectangular resonator. A filter with a compact size of 0.15 × 0.10 λg is obtained at a lowered cutoff frequency of 3.0 GHz, where λg is the corresponding guided wavelength. The proposed structure has been constructed on 5880 Rogers substrate with a thickness of 0.787 mm and a dielectric constant of 2.2. Additionally, equivalent lumped parameters were obtained, and a lumped equivalent circuit was created to explain how the suggested filter operated. The Electromagnetic (EM)-simulated results are in good agreement with the circuit-simulated and measured result. The various machine learning approaches such as artificial neural network, K-nearest neighbour, decision tree, random forest (RF), and extreme gradient boosting algorithms are applied to optimize the design, in which RF algorithms achieve more than 90% accuracy for predicting the S parameters of the ultrawideband filter.

International Journal of Microwave and Wireless TechnologiesVol. 16(8)
Vellore Institute of Technology University (IN), Atal Bihari Vajpayee Indian Institute of Information Technology and Management (IN)
Openalex Percentile: Top 30%
Microwave Engineering and Waveguides
0.63
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A compact ultrawide bandpass filter along notch characteristics with rectangular resonator through a machine learning approach — Dilip Kumar Choudhary, Pinku Ranjan, et al. · International Journal of Microwave and Wireless Technologies (2024) | TGRS Research Map | TGRS