Stochastic Analysis of the FXLMS-Based Narrowband Active Noise Control System
Why this work is in the frame
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Bibliographic record
Abstract
Noise signals generated by rotating machines such as diesel engines, cutting machines, fans, etc., may be modeled as noisy sinusoidal signals which can be successfully suppressed by narrowband active noise control (ANC) systems. In this paper, statistical performance of such a conventional filtered-x LMS (FXLMS)-based narrowband ANC system is investigated in detail. First, difference equations governing the dynamics of the system are derived in terms of convergence of the mean and mean squared estimation errors for the discrete Fourier coefficients (DFCs) of the secondary source. Steady-state expressions for DFC estimation mean square error (MSE) as well as the residual noise power are then developed in closed forms. A stability bound for the FXLMS in the mean sense is also derived. Extensive simulations of various scenarios are performed to demonstrate the validity of the analytical findings.
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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 | 0.001 |
| 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