Design of Wideband Bandpass Filter With Simultaneous Bandwidth and Notch Tuning Based on Dual Cross-Shaped Resonator
Bibliographic record
Abstract
In this paper, a wideband bandpass filter (BPF) with simultaneous bandwidth and notch tuning is proposed, by using a dual cross-shaped resonator (DCSR) with parallel-coupled three-line (PCTL) feeding. It is found that three intrinsic transmission zeros can be generated by the proposed DCSR, while two of the zeros are used for the implementation of passband edge zeros and the other one is for a notch. Three varactors are used to implement the bandwidth and notch tuning independently. These innovative integrated functions of both tunable bandwidth and notch in a single architecture are proposed for the first time. On the other hand, the PCTL can provide sufficiently strong coupling in the desired passband. The proposed BPF can achieve the bandwidth tuning with a fixed notch inside/outside the passband, and the bandwidth can also be kept unchanged when tuning a notch within the passband. The prototyped BPF centered at 6 GHz reports that the absolute bandwidth (ABW) can be varied from 2.5 to 5.8 GHz, while the fractional bandwidth (FBW) is tuned from 41.7% to 96.7% together with notch frequency tuning of 5.0 to 8.2 GHz. The experimental measurements are in good agreement with the theoretical analysis.
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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) | 0.001 | 0.001 |
| 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".