Estimation of varying bandwidth from multiple level crossings of stochastic signals
Bibliographic record
Abstract
This papers examines the problem of a local bandwidth recovery for non-stationary stochastic signals when the only available information is given in terms of level crossings. The use of multiple level crossings is a fundamental paradigm for the recently investigated event-based sampling approach. In fact, level crossings allows us to exploit local signal properties and to avoid unnecessarily fast sampling when the local signal intensity is low. The paper proposes the least-square based method for the local intensity estimation from level crossings for the class of signals being the time-warped version of the stationary and bandlimited Gaussian processes. This result is then related to the concept of the local mean bandwidth and finally to the local power bandwidth. The smooth convolution estimate of the local intensity is proposed and its positivity corrected version is introduced. The latter is achieved by the truncation argument and next by the method of alternating projections onto convex sets.
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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 | 0.001 |
| 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 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".