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Open AccessArticle

Novel Decomposition Technique on Rational-Based Neuro-Transfer Function for Modeling of Microwave Components

1
School of Microelectronics, Tianjin University, Tianjin 300072, China
2
Department of Electronics, Carleton University, Ottawa, ON K1S5B6, Canada
3
School of Computer Science and Technology, Guangdong University of Technology, Guangzhou 510006, China
*
Author to whom correspondence should be addressed.
Micromachines 2020, 11(7), 696; https://doi.org/10.3390/mi11070696
Received: 11 June 2020 / Revised: 8 July 2020 / Accepted: 13 July 2020 / Published: 17 July 2020
(This article belongs to the Section A:Physics)
The rational-based neuro-transfer function (neuro-TF) method is a popular method for parametric modeling of electromagnetic (EM) behavior of microwave components. However, when the order in the neuro-TF becomes high, the sensitivities of the model response with respect to the coefficients of the transfer function become high. Due to this high-sensitivity issue, small training errors in the coefficients of the transfer function will result in large errors in the model output, leading to the difficulty in training of the neuro-TF model. This paper proposes a new decomposition technique to address this high-sensitivity issue. In the proposed technique, we decompose the original neuro-TF model with high order of transfer function into multiple sub-neuro-TF models with much lower order of transfer function. We then reformulate the overall model as the combination of the sub-neuro-TF models. New formulations are derived to determine the number of sub-models and the order of transfer function for each sub-model. Using the proposed decomposition technique, we can decrease the sensitivities of the overall model response with respect to the coefficients of the transfer function in each sub-model. Therefore, the modeling approach using the proposed decomposition technique can increase the modeling accuracy. Two EM parametric modeling examples are used to demonstrate the proposed decomposition technique. View Full-Text
Keywords: decomposition; microwave components; neural networks; parameter extraction; parametric modeling; rational-based transfer function decomposition; microwave components; neural networks; parameter extraction; parametric modeling; rational-based transfer function
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MDPI and ACS Style

Zhao, Z.; Feng, F.; Zhang, J.; Zhang, W.; Jin, J.; Ma, J.; Zhang, Q.-J. Novel Decomposition Technique on Rational-Based Neuro-Transfer Function for Modeling of Microwave Components. Micromachines 2020, 11, 696.

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