Application of Lifting Wavelet Packet Decomposing Algorithm in EMC Simulation of Automobile
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this paper is to extract data features and denoise the interference excitation source in vehicle electromagnetic compatibility test. The lifting wavelet packet algorithm inherits the multi-resolution characteristics of the classic (first generation) wavelet transform. The transform is only carried out in the time domain, which can achieve in situ operation. It has the advantages of small space occupation, fast transformation speed, easy inversion, etc. It can use energy conservation criteria to extract characteristic energy to identify the conducted interference sources in the vehicle, and the obtained characteristic spectrum is used as the modulation array of the excitation source of the vehicle numerical simulation. In this paper, the collected interference signals are decomposed into lifting wavelet packets, and then the characteristic energy is extracted to identify the conducted interference sources in the vehicle. Signal to noise ratio (SNR), root mean square error (RMSE) and peak error (PE) are used to verify the consistency between the simulation signal and the original signal. The results show that the lifting wavelet packet algorithm has a strong ability to identify the conducted interference sources in the vehicle.
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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) | 0.001 | 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