Hardware software co-simulation of a digital EMI filter using Xilinx system generator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mitigation of electromagnetic inference (EMI) is currently a challenge for scientists and designers in order to cope with electromagnetic compatibility (EMC) compliance in switching mode power supply (SMPS) and ensure the reliability of the whole system. Standard filtering techniques: passive and active ones present some insufficiency in terms of performance at high frequencies (HF) because analog components would no longer be controllable and this is mainly due to their parasitic elements. So developing EMI digital filters is very interesting, especially with the embedment of a machine control system on a field programmable gate array (FPGA) chip. In this paper, we present a design of an active digital EMI filter (ADF) to be integrated in a drive train system of an electric vehicle (EV). Hardware design as well as FPGA implementation issues have been presented to prove the efficiency of the developed digital filtering structure.
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.
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