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Millimeter-wave Micromachined Filter Design by Artificial Neural Network Modeling Technique

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Abstract

This paper presents a design approach for a 34 GHz λ/2 resonator micormachined bandpass filter by using the artificial neural network (ANN) modeling technique. Three important dimensions of the filter layout are used to capture critical input-output relationships in the ANN model. Once fully developed, the ANN model has been shown to be as accurate as an EM simulator and much more efficient computationally in the design optimization of the filter.

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Acknowledgement

This work was supported by the National Natural Science Foundation of China and funding from Hutech21 company in South Korea. The authors are grateful to the work of Yang Lv and Bin Yang (Tsinghua University).

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Authors and Affiliations

  1. School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing, China

    Xiu Ping Li

  2. Radio Engineering Department, Southeast University, Nanjing, China

    Jian Jun Gao

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  1. Xiu Ping Li
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  2. Jian Jun Gao
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Correspondence to Xiu Ping Li.

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Li, X.P., Gao, J.J. Millimeter-wave Micromachined Filter Design by Artificial Neural Network Modeling Technique. Int J Infrared Milli Waves 28, 541–546 (2007). https://doi.org/10.1007/s10762-007-9227-7

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  • DOI: https://doi.org/10.1007/s10762-007-9227-7

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