Scaling-Basis Chirplet Transform
Bibliographic record
Abstract
In this study, a novel time-frequency (TF) analysis method, referred to as the scaling-basis chirplet transform (SBCT), is developed by extending the conventional chirplet transform. This method includes a replacement kernel function that can vary the chirp rate with frequency and time by scaling the TF basis at and around the corresponding time center. This enables the corresponding chirplets to accurately match the targeted slopes for every trajectory of a multicomponent signal and within any window length. Therefore, the TF representation obtained via the SBCT can achieve significantly higher energy concentrations even for multicomponent signals with close-spaced frequencies and high levels of background noise. The effectiveness of the proposed SBCT approach was demonstrated by analyzing a numerical multicomponent signal and a vibration signal obtained from a gearbox test rig. Both numerical and experimental results showed that the SBCT can satisfactorily handle multicomponent signals with nonlinear frequency trajectories, close-spaced frequencies, and noisy backgrounds, demonstrating its superiority.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".