Comparative evaluation of the dual transform domain echo canceller for DMT-based systems
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Bibliographic record
Abstract
In DMT-based communication systems where full-duplex transmission is required, digital echo cancellers are employed to cancel echo by means of adaptive filters. In order to reduce the computational complexity of these cancellers, the structure of the Toeplitz matrix containing the transmitted signal is usually exploited to transform the time domain signals and perform the emulation and adaptive update in a more convenient domain (e.g. frequency domain). In this paper, we consider a recently proposed dual transform domain echo canceller, which is based on the general decomposition of the data Toeplitz matrix. A comprehensive comparative performance evaluation of the proposed method with the existing methods is provided. This evaluation includes the comparison of the convergence curves and computational cost of the algorithms. The comparison shows that the proposed canceller achieves a faster convergence with a low error floor with no increase in the complexity.
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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