Bibliographic record
Abstract
The performance of an active noise control system employing digital signal processing is influenced by the analog signal amplitudes within the input and output analog-digital (A/D) and D/A converters, and hence is sensitive to the sound pressure being controlled. While compensation is commonly provided within the algorithm for variations in input power (e.g., by normalizing the adaptation step size), the full dynamic range of the A/D and D/A subsystems is usually not realized. An analog gain control system has been developed consisting of linked, reciprocal variable gain amplifiers, so arranged that the changes in signal amplitude at the A/Ds and D/As are smaller than the changes in sound pressure of the acoustic system being controlled. The gain control system operates on the error and secondary source signals so as to maintain the error path impulse response unchanged. In this way the gain changes are transparent to the digital controller. The application of the method to an adaptive feed-forward active noise control system for a circumaural hearing protector, or headset, will be described. [Work supported by the Defence and Civil Institute of Environmental Medicine.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".