Application of embedding dimension estimation to Volterra series-based behavioral modeling and predistortion of wideband RF power amplifier
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Bibliographic record
Abstract
This paper expounds the systematic modeling of the behavior of radio frequency ( RF ) power amplifiers (PAs) exhibiting nonlinear, dynamic behavior. The approach begins with an analysis of the PA output signal to deduce the minimum embedding parameters required to accurately model its response, particularly the nonlinearity order and memory effects depth. The knowledge of the RF PA is then exploited in limiting the number of kernels consequently addressing the complexity of the Volterra series which has been the key hindrance to its wider practical adoption. In the proposed Volterra series model, performance is assessed and compared to memory polynomial model and dynamic deviation reduction Volterra models when used to linearize different high-power amplifiers driven with wideband signals of bandwidth up to 40 MHz. Significant linearization performance is achieved using a reduced number of kernels.
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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 | 0.000 | 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 it