Multichannel nonlinear phase analysis for time-frequency data fusion
Why this work is in the frame
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Bibliographic record
Abstract
A general method for time delay of arrival (TDOA) estimation for time-frequency information fusion is analyzed. This technique, for which the generalized cross correlation method and histogram methods are special cases, results in a low TDOA estimation error and high efficiency in computation. The proposed method relies on a non-linear phase-error selector function, which acts as a reward and punish method for the phase error at each frequency. Three different selector function candidates, consisting of cosine, rectangular, and triangular functions are analyzed using simulations. In the presence of Gaussian noise, the rectangular selector function performs better than the cosine at signal-to-noise ratios (SNRs) higher than 10dB while for lower SNRs the cosine function performs better. With speech noise, the cosine function, which corresponds to the generalized cross correlation technique, has higher anomaly percentages and higher root-mean-square errors than the rectangular function. This suggests that in general, the rectangular selector function, which can be computed more easily than the cosine selector function, is superior technique to the generalized cross correlation method for real-time applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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