FPGA Implementation of a Novel Compensation Technique for EER Amplifiers
Bibliographic record
Abstract
This paper examines a practical method to reduce the spectral distortion at the output of an envelope elimination and restoration (EER) power amplifier (PA). The EER amplifiers utilized in terrestrial amplitude modulation (AM) radio broadcast transmitters are affected by non-linear and memory effects; the proposed compensation method exploits the source of these effects in real-world amplifiers. Specifically, using a new feed forward configuration for pre-processing the amplifier input, the algorithm predicts the PA output in real-time using its realistic behavior modeled through dynamic differential equations. The compensation method implemented at the base band considers the effects created by the most critical components of the EER amplifier, i.e, band-limiting of the envelope by the reconstruction filter and a non-linear load applied at the output of the reconstruction filter. The performance improvements of the proposed method are measured by its ability to reduce total harmonic distortion (THD) at the output of the system. Taking advantage of the efficient utilization of available computational resources, the feasibility of implementing this system is verified using a FPGA platform.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".