Design of a narrow dual‐band BPF with an independently‐tunable passband
Bibliographic record
Abstract
Using polygonal resonators and bended lines, a new type of dual‐band bandpass filter (BPF) is presented generating a fixed passband centred at 2.70 ( f 01 ) and an independently‐electronically tunable passband ( f 02 ) which can be tuned between 3.65 and 6.51 GHz (56% tuning range). The measured results indicate that the return losses of both passbands are >21 dB throughout the tuning range. Furthermore, the use of bended lines leads to extremely small size of , where is the guided wavelength at the lowest working frequency ( f 01 ). The proposed BPF also benefits from an ultra‐wide upper stopband from 7.03 up to 14.41 GHz (based on 21 dB points), suppressing unwanted signal by more than 21 dB considered as a positive point. The filter prototype is investigated in four design stages with the LC analysis to support the design process theoretically and fabrication results to validate the design practically.
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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) | 0.001 | 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 | 0.001 | 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".