Convolutional Neural Networks as Asymmetric Volterra Models Based on Generalized Orthonormal Basis Functions
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Bibliographic record
Abstract
This paper introduces a convolutional neural network (CNN) approach to derive Volterra models of dynamical systems based on generalized orthonormal basis function (GOBF)-Volterra. The approach derives the parameters of the model through a CNN and the neural network's learned weights represent the poles of a system. Simulation results show that the parameters of the system can be exactly recovered when no noise is applied. Furthermore, when noise is present, the errors in the parameters are very small for both the linear and nonlinear cases. Finally, the approach is used to identify the model of a quadcopter using data from actual flight tests. Comparisons with previous works demonstrate that CNNs can be satisfactorily used for the identification of dynamical systems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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