Sammenlign metoder

	FxLMS Aktiv Støjreduktion	Lineær prædiktiv kodning
Fagområde	Akustik	Akustik
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	1975	1975
Ophavsperson	Bernard Widrow, Samuel Stearns	Freddy Burg, John Makhoul
Type	Adaptive noise cancellation algorithm	Predictive speech coding and analysis
Oprindelig kilde	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.
Aliasser	FxLMS, filtered-x LMS, active noise cancellation, ANC	LPC, autoregressive model, speech prediction, vocal tract modeling
Relaterede	5	5
Resumé	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.