Active noise cancellation: Where does the extra power go?
Bibliographic record
Abstract
Active noise cancellation (ANC) is a method of reducing an undesired signal, i.e., noise, by introducing an “antinoise” signals from secondary sources. A fundamental issue for noise cancellation is the destiny of the excess noise power. The noise and the anti-noise sum to create at least twice the power of the original noise, and with the summed power minimized at the site of the cancellation, the excess power must appear elsewhere - often defeating the purpose of the ANC. While ANC is best known for acoustic waves, including vibration control, very similar techniques hold for the signals of electromagnetic waves as used in diversity and MIMO communications antennas, electromagnetic cloaking, and other signal processing such as polarization cancellers, equalizers, multi-user detectors, in communications, sonar and radar. We present here a simple and insightful tour of the cancellation mechanisms of ANC, and the destiny of the excess power generated. For a closed, lossless situation, we demonstrate using a transmission line formulation that both the primary noise and secondary anti-noise are reflected back to their own sources, and dissipated in their source impedances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".