Cross coupled signal controlled constrained null filter and separation of superimposed frequency modulated sinusoids
Why this work is in the frame
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Bibliographic record
Abstract
The problem of separation of superimposed frequency modulated (FM) sinusoids is addressed. A cross-coupled signal controlled constrained null filter (CC-SCCNF) is proposed to separate the individual signal from the sum of a number of FM signals whose power spectra may overlap. An advantage of the proposed CC-SCCNF is that one does not have to make any assumption on the mixture of the superimposed FM signals, other than that the number of FM signals is a priori known. A necessary condition is described in terms of the trajectories of the SCCNF coefficients. These trajectories are monitored by measuring the instantaneous Euclidean distance between any two SCCNF trajectories. A proof of the CC-SCCNF convergence to a unique solution for the separation of signals is provided. Several computer simulation results are also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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) | 0.001 | 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