Application of the Wavelet Packet Transform for the Identification of Chaotic Signals in the Current-Programmed DC/DC Boost Converters
Bibliographic record
Abstract
The wavelet packet transform (WPT), a digital realization of the wavelet transform (WT), has been used in this work for identifying and characterizing sub-harmonic and chaotic signals in a current-mode-controlled boost converter. The operation of the boost converter under current-programmed control is explained, and some computer-generated waveforms are presented in order to illustrate the various possible operating regimes of the current-programmed dc/dc converters. Samples of the state variables of different periodic and chaotic operating conditions of the converter are decomposed up to a certain level of resolution of the wavelet packet tree using a selected mother wavelet in order to characterize different sub-harmonic and chaotic signals occurred in the converter. The wavelet-transformed coefficients of the sampled state variables of different frequency sub bands of the wavelet packet tree are able to differentiate effectively between different periodic and chaotic operating conditions of the converter.
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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".