Title | An Unsupervised Microwave Filter Design Optimization Method Based on a Hybrid Surrogate Model-Assisted Evolutionary Algorithm |
Author | |
Publication Years | 2022
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DOI | |
Source Title | |
ISSN | 1557-9670
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EISSN | 1557-9670
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Volume | PPIssue:99Pages:1-12 |
Abstract | In resonator-coupled bandpass filter 3D design, it is a routine that the filter optimization methods are guided/supervised by designers' experience to carry out an iterative design optimization process. To realize automated or unsupervised filter 3D design optimization, a new method, called hybrid surrogate model-assisted evolutionary algorithm for filter optimization (H-SMEAFO), is proposed. H-SMEAFO aims to automatically obtain a highly optimal filter 3D design without designers' interaction (i.e., unsupervised) and is also not restricted to certain kinds of filter structures. In H-SMEAFO, the key innovations include a hybrid response feature-based objective function and a hybrid surrogate model-assisted global optimization algorithm; both are designed bespoke for filter design landscape characteristics. The performance of H-SMEAFO is demonstrated by an 8th-order dual-band waveguide filter with four transmission zeros and a 6th-order waveguide filter with two transmission zeros, for which, unsupervised design optimization does not appear to be possible using existing methods. Numerical results show the effectiveness and advantages of H-SMEAFO. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
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SUSTech Authorship | Others
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WOS Research Area | Engineering
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WOS Subject | Engineering, Electrical & Electronic
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WOS Accession No | WOS:000890814200001
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Publisher | |
Data Source | IEEE
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PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9960817 |
Citation statistics |
Cited Times [WOS]:1
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/414586 |
Department | Department of Electrical and Electronic Engineering |
Affiliation | 1.James Watt School of Engineering, University of Glasgow, Glasgow, U.K. 2.Electronic and System Engineering, School of Electrical, University of Birmingham, Birmingham, U.K. 3.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China |
Recommended Citation GB/T 7714 |
Liyuan Xue,Bo Liu,Yang Yu,et al. An Unsupervised Microwave Filter Design Optimization Method Based on a Hybrid Surrogate Model-Assisted Evolutionary Algorithm[J]. IEEE Transactions on Microwave Theory and Techniques,2022,PP(99):1-12.
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APA |
Liyuan Xue,Bo Liu,Yang Yu,Qingsha S. Cheng,Muhammad Imran,&Tianrui Qiao.(2022).An Unsupervised Microwave Filter Design Optimization Method Based on a Hybrid Surrogate Model-Assisted Evolutionary Algorithm.IEEE Transactions on Microwave Theory and Techniques,PP(99),1-12.
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MLA |
Liyuan Xue,et al."An Unsupervised Microwave Filter Design Optimization Method Based on a Hybrid Surrogate Model-Assisted Evolutionary Algorithm".IEEE Transactions on Microwave Theory and Techniques PP.99(2022):1-12.
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