A constant-Q tunable combline bandpass filter using angular tuning technique
Bibliographic record
Abstract
This paper presents the design and implementation of a high-Q bandpass filter using a tuning technique that maintains constant Q value over a relatively wide tuning range. The traditional technique for tuning combline filters is achieved by changing the gap between the post and the tuning disk. Such technique is known to yield a Q value that degrades considerably at the lower edge of the tuning range. The proposed angular tuning technique shows a 25% improvement in Q value at the lower edge of the tuning range, in comparison to what is typically achieved using the traditional tuning technique. Using the proposed angular tuning technique, a 1% bandwidth 2-pole filter is designed, fabricated and tested with a 430MHz tuning range at a center frequency of 3.6 GHz. The measured insertion loss is changing between 0.25 and 0.33dB. The filter is integrated with miniature piezoelectric motors, demonstrating almost a constant insertion loss over the tuning range.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".