The Discrete Stockwell Transforms for Infinite-Length Signals and Their Real-Time Implementations
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Bibliographic record
Abstract
The various forms of the Stockwell transforms (ST) introduced in the literature have been developed for off-line signal processing on finite-length signals. However, in many applications such as audio, medical or radar signal processing, signals to be analyzed are of large sizes or received in real-time, time-frequency representations of such a signal cannot be calculated using the entire signal. The common approach is to calculate the spectrum segment-by-segment. This may result obvious boundary effects or lose absolute-referenced phase information in their time-frequency representations. In this paper, new formulations of the discrete ST for infinite-length signals are proposed. Based on the new definitions, fast algorithms are implemented using the fast Fourier transform. Our proposed computational schemes make it possible to process an infinite-length/large size signal segment-by-segment at low computational cost without any boundary effects. More importantly, the absolute-referenced phase information is reserved in this approach. These properties make the infinite-length STs more suitable for real-time signal processing.
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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) | 0.000 | 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