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MOR-Based Neuro-TF

delete2025-02-01
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PRE
AI
马历 cover
马历 (Li Ma)
J
Jingyi Feng
J
Jianan Zhang *
Q
Qi‐Jun Zhang
DOI:10.1109/MMM.2024.3486584delete
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Abstract

Abstract

En 中文
Neuro-transfer function (neuro-TF) approaches are useful instruments for electromagnetic (EM) parameterized modeling of microwave passive components. A vector fitting technique is commonly used to obtain the TF coefficients from the EM responses utilized in conventional neuro-TF approaches. However, the use of this method can introduce an order-changing issue, where the TF orders vary across different regions of the design parameter space. Recently, an alternative neuro-TF method has been proposed, which employs a model-order reduction (MOR)-based TF. Instead of utilizing a vector fitting process, the MOR process acquires the poles/zeros (rational coefficients) during full-wave EM simulations. The MOR technique ensures a consistent TF order across different geometric parameter values. This article provides an extensive overview of the most recent developments in MOR-based neuro-TF techniques. In particular, the approach is examined in two formats: the rational format and the pole/zero format. The former technique provides a solution to the problem of order-changing in conventional vector fitting-based neuro-TF, but it still has problems with poles/zeros being mismatched. Thus, the latter format, an EM sensitivity-based approach, has been developed to guarantee the continuity of the poles/zeros across different geometric training samples to address the mismatch problem.
Keywords:
EM
NETWORKS
LANCZOS
PADE

Journal

IEEE Microwave Magazine cover
IEEE Microwave Magazine
IF:
2.6
Papers:
3.2K
Citations:
3.1K

Organization

T
tianjin university
Scholars:
7.9W
Papers: 5.7W
Citations: 88
S
southeast university - china
Scholars:
5.3W
Papers: 4.9W
Citations: 57
C
carleton university
Scholars:
7.5K
Papers: 8.3K
Citations: 5
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