ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

FxLMS 능동 소음 제어×Cepstral Analysis×
분야음향학음향학
계열Process / pipelineProcess / pipeline
기원 연도19751963
창시자Bernard Widrow, Samuel StearnsBogert, Healy, Tukey
유형Adaptive noise cancellation algorithmSpectral decomposition method
원전Widrow, 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 ↗
별칭FxLMS, filtered-x LMS, active noise cancellation, ANCcepstrum, MFCC, mel-frequency cepstral coefficients, spectral analysis
관련55
요약The 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.
ScholarGate데이터셋
  1. v1
  2. 3 출처
  3. PUBLISHED
  1. v1
  2. 3 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: FxLMS Active Noise Control · Cepstral Analysis. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare