| Autor: |
Shuxia Yan, Fengqi Qian, Chenglin Li, Jian Wang, Xu Wang, Wenyuan Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Micromachines, Vol 14, Iss 8, p 1600 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2072-666X |
| DOI: |
10.3390/mi14081600 |
| Popis: |
In this paper, an improved empirical formula modeling method using neuro-space mapping (Neuro-SM) for coupled microstrip lines is proposed. Empirical formulas with correction values are used for the coarse model, avoiding a slow trial-and-error process. The proposed model uses mapping neural networks (MNNs), including both geometric variables and frequency variables to improve accuracy with fewer variables. Additionally, an advanced method incorporating simple sensitivity analysis expressions into the training process is proposed to accelerate the optimization process. The experimental results show that the proposed model with its simple structure and an effective training process can accurately reflect the performance of coupled microstrip lines. The proposed model is more compatible than models in existing simulation software. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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