A convex method for selecting optimal Laguerre filter banks in system modelling and identification
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Bibliographic record
Abstract
When approximating dynamic systems with Laguerre Basis Functions it is important to tune the Laguerre pole such that the expansion is both parsimonious and accurate. The sum of squared error (SSE) objective function has many local minima and therefore cannot be optimized directly. Two alternative objective functions have been proposed in the literature: an asymptotically optimal objective function, and an enforced convergence criterion (ECC). Currently both objective functions can only be evaluated in a system modelling framework. Two questions that will be addressed in this paper are: (1) does minimizing the ECC lead to a good estimate of the optimal Laguerre pole position (in the SSE sense), and (2) is it possible to use the ECC in a system identification framework?
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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 | 0.000 |
| 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