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Kontrolli Aktiv i Zhurmës FxLMS×Analiza Cepstrale×
FushaAkustikëAkustikë
FamiljaProcess / pipelineProcess / pipeline
Viti i origjinës19751963
KrijuesiBernard Widrow, Samuel StearnsBogert, Healy, Tukey
LlojiAdaptive noise cancellation algorithmSpectral decomposition method
Burimi themeluesWidrow, B., & Stearns, S. D. (1975). Adaptive signal processing for active vibration and noise control. IEEE Transactions on Acoustics, Speech, and Signal Processing, 23(5), 440–453. DOI ↗Bogert, B. P., Healy, M. J., & Tukey, J. W. (1963). The quefrency alanysis of time series for echoes: cepstrum, pseudo-autocovariance, cross-cepstrum, and saphe cracking. In Time Series Analysis Research Papers (pp. 209–243). Wiley. link ↗
Emërtime të tjeraFxLMS, filtered-x LMS, active noise cancellation, ANCcepstrum, MFCC, mel-frequency cepstral coefficients, spectral analysis
Të lidhura55
PërmbledhjaThe Filtered-x Least Mean Squares (FxLMS) algorithm is an adaptive filter used in active noise control (ANC) systems to reduce unwanted sound by generating anti-noise. Pioneered by Widrow and Stearns in 1975 and refined by Eriksson and colleagues, FxLMS is the most widely deployed algorithm in commercial noise-canceling headphones, hearing aids, automotive cabins, and industrial noise barriers. It works by continuously learning the acoustical path and dynamically adjusting a canceling signal in real time.Cepstral analysis is a spectral analysis technique that decomposes signals into independent components by inverting the log-magnitude spectrum. Pioneered by Bogert, Healy, and Tukey in 1963, cepstral analysis reveals periodic structure in spectra (pitch, echo patterns) and separates source excitation from filter response. Mel-frequency cepstral coefficients (MFCCs) derived from cepstral analysis are the most widely used features in automatic speech recognition, speaker verification, and audio analysis.
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  1. v1
  2. 3 Burimet
  3. PUBLISHED

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ScholarGateKrahasoni metodat: FxLMS Active Noise Control · Cepstral Analysis. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare