Tunable Dielectric Resonator Bandpass Filter With Embedded MEMS Tuning Elements
Bibliographic record
Abstract
This paper presents a novel approach for constructing a tunable dielectric resonator bandpass filter by using the microelectromechanical system (MEMS) technology. The tunability is achieved by unique MEMS tuning elements to perturb the electrical and magnetic fields surrounding the dielectric resonators. The use of such elements as a tuning mechanism results in a wide tuning range at a relatively low tuning voltage and fast tuning speed. A three-pole tunable dielectric resonator bandpass filter is designed, fabricated, and tested. The experimental filter has a center frequency of 15.6 GHz, a 1% relative bandwidth, and an unloaded Q of 1300. A tuning range of 400 MHz is obtained by using MEMS tuning elements with 2 mmtimes2 mm tuning disks. The measured results demonstrate the feasibility of the proposed concept
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".