Empirical and deterministic approach for the optimization of wideband RF power amplifiers' behavior modeling and predistortion structure
Bibliographic record
Abstract
Abstract This article presents an approach to determining the smallest number of coefficients of a Parallel Hammerstein (PH) model to reduce the development complexity of wideband RF power amplifiers' (PA) modeling and predistortion schemes. The visualization of the impulse responses of the different filters of the PH yields a systematic and single‐iteration approach for determining the optimal modeling structure, for example, filters' lengths. The approach was used to determine an optimal structure that linearizes the response of a 400‐watt LDMOS Doherty PA driven with a four carrier WCDMA signal. In the experiments conducted, the number of coefficients in the PH was reduced by about a factor of 2.5 without compromising its modeling and linearization performance. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:116–118, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25660
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".