Сравнение методов

	Активное шумоподавление с использованием алгоритма FxLMS	Линейное предсказание (Linear Predictive Coding)
Область	Акустика	Акустика
Семейство	Process / pipeline	Process / pipeline
Год появления	1975	1975
Автор метода	Bernard Widrow, Samuel Stearns	Freddy Burg, John Makhoul
Тип	Adaptive noise cancellation algorithm	Predictive speech coding and analysis
Основополагающий источник	Widrow, 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.	Makhoul, J. (1975). Linear prediction: A tutorial review. Proceedings of the IEEE, 63(4), 561–580.
Другие названия	FxLMS, filtered-x LMS, active noise cancellation, ANC	LPC, autoregressive model, speech prediction, vocal tract modeling
Связанные	5	5
Сводка	The 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.	Linear Predictive Coding (LPC) is a powerful signal processing technique for modeling and compressing speech by assuming each speech sample can be predicted from a linear combination of previous samples. Pioneered by Burg and Makhoul in the 1970s, LPC is the foundation of speech codecs, speech synthesis, speaker recognition, and speech enhancement. LPC exploits the time-correlated structure of speech to achieve high compression ratios and enable efficient parameter extraction.