Tunable Dual-Band Filters and Diplexers Using a Single Tuning Element
Bibliographic record
Abstract
This article proposes a novel design for a tunable coaxial dual-band filter capable of simultaneously changing the center frequency of both bands. The resonator consists of a metallic rod with two fins of different dimensions inserted inside a cavity housing. Each fin represents a$(\lambda /4)$resonator that is responsible for covering one band. The housing is shaped to change the capacitive loading on the two$(\lambda /4)$resonators and change their resonance frequencies as the rod rotates inside the housing. Specific iris shapes are designed to provide proper coupling between adjacent dual-band resonator and realize the tunable dual-band filter. A feature of the proposed design is that different shapes of housings can result in different directions of movement of the passbands within each range. Additionally, this design utilizes a single tuning element in the middle of the housing to rotate the resonators, independently of the filter’s order. To verify this concept, two reconfigurable dual-band six-pole filters were designed and tested. The only difference between these two designs is the shape of their housings, which demonstrates different directions of movement of the two passbands. The proposed concept demonstrates the feasibility of realizing tunable dual-band filters using a single tuning element for the first time. This article also shows how the concept can extended to realize a tunable diplexer with a single tuning element.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".