Multiple oscillations detection in control loops by using the DFT and Raleigh distribution ★ ★This work was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada; the National Natural Science Foundation of China [61174161, 61304141, 61375077]; the specialized Research Fund for the Doctoral Program of Higher Education of China [20130121130004]; and the Fundamental Research Funds for the Central Universities in China [201212G005].
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Bibliographic record
Abstract
This work introduces an oscillation detection method by analyzing the magnitude of signal after the discrete Fourier transform (DFT). Properties of Raleigh distribution are used to calculate a threshold in order to detect multiple oscillations simultaneously. The proposed algorithm is able to detect oscillations in presence of colored noise based on a statistical test. Two simulation examples are provided to verify the effectiveness of the method.
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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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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