Predistortion technique for cross-coupled filters and its application to satellite communication systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a novel adaptive predistortion technique for general cross-coupled microwave/RF filters with improved insertion loss and group-delay equalization. The method enables many potential applications of an almost abandoned technique, and permits a lower Q implementation technology to emulate the performance of a higher Q filter. 10-4-4 filters were built and tested at C- and Ku-band to verify the validity of the new method. The impact to satellite communication channels was also analyzed. Another novel concept of over-predistortion was proposed and evaluated and should lead to significant improvement for applications such as satellite transponder input multiplexers, where insertion loss can be traded off for in-band flatness, mass, volume, and even overall system performance.
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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 | 0.001 | 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 it