FIR modelling for errors‐in‐variables/closed‐loop systems by exploiting cyclo‐stationarity
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Finite impulse response (FIR) modelling of errors‐in‐variables/closed‐loop systems by correlation analysis usually yields biased estimates due to the additive noises on inputs and outputs. A non‐parametric approach, the cyclic correlation analysis (CCRA), provides asymptotically unbiased and consistent estimates. The main feature of the CCRA is to eliminate the adverse effects of stationary noises by exploiting cyclo‐stationarity that may exist naturally or be induced artificially. A complete study of the CCRA is developed, including the statistical performance of the estimated FIR model. Frequency‐domain expressions of the statistical performance provide guidelines in designing a class of cyclo‐stationary signals for modelling. Effectiveness and properties of the CCRA are validated and illustrated by numerical examples. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.000 | 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