Flexible ultra‐high transformation ratio‐based dual‐band impedance transformer and its applications in a T‐junction power divider
Bibliographic record
Abstract
Abstract A design scheme is presented for an all‐pass coupled‐line (APCL)‐based dual‐band impedance‐matching network. Salient features include a highly flexible frequency ratio (r) (high of 15 and low of 1.2) and impedance transformation ratio (k) (high of 9 and low of 0.2) simultaneously at two arbitrary, uncorrelated frequencies of interest. The design strategy consists of two APCL sections and a stub that prove to be simple and easy to prototype. Detailed mathematical modelling and graphical interpretations have been presented. Closed‐form design equations have been developed and backed up with design examples. Two dual‐band T‐junction power dividers (TPDs) have been designed to demonstrate the application of the proposed impedance transformer at two widely separated frequencies. RO4350 B‐ and RO5880‐based prototypes have been fabricated for both the matching network and the TPD to validate the proposed theory. The measurement results demonstrate an achievable frequency ratio of 15 and an impedance transformation ratio of 9 in simultaneous operation mode.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".