A Variable Step-Size FXLMS Algorithm for Narrowband Active Noise Control

In this paper, a variable step-size filtered-x LMS (VSS-FXLMS) algorithm is proposed for a typical narrowband active noise control system. The new algorithm converges much faster than the conventional FXLMS algorithm does, and indicates a convergence rate quite similar to that of the filtered-x recu...

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Vydané v:IEEE transactions on audio, speech, and language processing Ročník 21; číslo 2; s. 301 - 312
Hlavní autori: Huang, Boyan, Xiao, Yegui, Sun, Jinwei, Wei, Guo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway, NJ IEEE 01.02.2013
Institute of Electrical and Electronics Engineers
Predmet:
Algorithm design and analysis
Applied sciences
Convergence
Convergence rate
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Finite impulse response filter
FXLMS
FXRLS
Information, signal and communications theory
Least squares approximation
Narrowband
narrowband active noise control (NANC)
Noise
Signal and communications theory
Signal processing algorithms
Signal, noise
Telecommunications and information theory
variable step size
Performance evaluation
Infinite impulse response filter
FXLMS
FXRLS
Narrow band noise
Background noise
Algorithm
Computational complexity
Variable step method
Convergence speed
Simulation
Least squares method
Convergence rate
Stationary noise
Active noise control
narrowband active noise control (NANC)
Least mean squares methods
variable step size
ISSN:1558-7916, 1558-7924
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Popis
Shrnutí:In this paper, a variable step-size filtered-x LMS (VSS-FXLMS) algorithm is proposed for a typical narrowband active noise control system. The new algorithm converges much faster than the conventional FXLMS algorithm does, and indicates a convergence rate quite similar to that of the filtered-x recursive least square (FXRLS) algorithm in stationary noise environments. It also considerably outperforms these two existing algorithms in nonstationary situations. The proposed algorithm requires some more computations as compared with the FXLMS algorithm; however, its computational complexity is significantly less than that of the FXRLS algorithm. Numerous simulations for stationary and nonstationary scenarios are conducted to demonstrate the superior performance of the proposed VSS-FXLMS algorithm as compared with the FXLMS and the FXRLS algorithms.
ISSN:1558-7916
1558-7924
DOI:10.1109/TASL.2012.2223673