Multilayer Cross‐Coupled Substrate Integrated Waveguide Filter With Quasi‐Elliptic Response and Wide Stopband
Bibliographic record
Abstract
ABSTRACT Substrate integrated waveguide (SIW) filters usually employ cross‐coupling to produce quasi‐elliptic responses to achieve steep selectivity near the passband. But the added cross‐coupling enables additional transmission of spurious modes and facilitates the generation of spurious passbands, which degrades stopband selectivity and is challenging to address effectively without cascading additional filters or using hybrid resonant structures. This letter proposes a solution. By specially arranging the positions of the coupling structures in a TE 101 cross‐coupled SIW filter, TE 102 and TE 201 cannot couple/transmit through both the main and cross‐coupling structures. Furthermore, by using a multilayer structure and exchanging the position of the electric coupling, the superior shielding and quality factor of SIW can be maintained. And these operations can be performed without affecting the TE 101 quasi‐elliptic response. As a result, the proposed multilayer cross‐coupled SIW filter can effectively achieve a wide stopband in addition to the quasi‐elliptic response, and is suitable for integration in high‐performance and high‐frequency applications. It should be effective for developing SIW filters in wireless and microwave circuits and systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".