Analysis and minimization of L/sub 2/-sensitivity for linear systems and two-dimensional state-space filters using general controllability and observability Gramians
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Bibliographic record
Abstract
A novel expression for the evaluation of L/sub 2/-sensitivity is developed for the cases of linear discrete-time systems, linear continuous-time systems, and two-dimensional (2-D) state-space digital filters. This is accomplished by introducing the concept of general controllability and observability Gramians in each case. Moreover, the L/sub 2/-sensitivity measures obtained here contain the conventional L/sub 1//L/sub 2/-sensitivity measures as a special case. An iterative procedure for constructing the optimal coordinate transformation matrix that minimizes the L/sub 2/-sensitivity measure is then presented in each case. This procedure is advantageous since the initial estimate and the estimate at each iteration can be calculated analytically. Finally, three numerical examples are given to illustrate the utility of the proposed techniques.
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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