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.

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Keywords Decomposition, Microwave components, Neural networks, Parameter extraction, Parametric modeling, Rational-based transfer function
Persistent URL
Journal Micromachines
Zhao, Z. (Zhihao), Feng, F. (Feng), Zhang, J. (Jianan), Zhang, W. (Wei), Jin, J. (Jing), Ma, J. (Jianguo), & Zhang, Q.J. (2020). Novel decomposition technique on rational-based neuro-transfer function for modeling of microwave components. Micromachines, 11(7). doi:10.3390/mi11070696