Multilayer SIW Dual-Band Filters with Independent Band Characteristics and High Selectivity
Bibliographic record
Abstract
Abstract This work presents an approach to developing dual-mode dual-band substrate integrated waveguide (SIW) bandpass filter based on multilayer process. TE102/TE201 and TE101/TE102 modes are used to feature the two passbands, respectively. To begin with, large range of band location ratios are decided by the effective dimension of the SIW resonator. With reference to the field distribution, independent coupling schemes of the dual-modes are then realized by slots or circular apertures etched on the middle metal layer. It allows to not only introduce a large design freedom of bandwidth but also keep compactness. Finally, source-load and mixed couplings are deployed to produce transmission zeros around the passband in providing a sharp selectivity in the two filters, respectively. The details to independently control the center frequencies and bandwidth of two passbands are also presented. A two-order double-layered and a triple-layered SIW dual-band bandpass filter are prototyped to evaluate the proposed design approach, respectively. Results show a good agreement between simulations and measurements. The proposed filter exhibits flexible design freedom, high selectivity as well as good out-of-band rejection.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".