Variable step-size LMS algorithm: new developments and experiments

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

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A noise resilient variable step-size LMS algorithm

Signal Processing ◽

10.1016/j.sigpro.2007.09.015 ◽

2008 ◽

Vol 88 (3) ◽

pp. 733-748 ◽

Cited By ~ 41

Author(s):

Márcio Holsbach Costa ◽

José Carlos Moreira Bermudez

Keyword(s):

Lms Algorithm ◽

Variable Step Size ◽

Step Size ◽

Variable Step

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Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

Noise Control Engineering Journal ◽

10.3397/1/376914 ◽

2021 ◽

Vol 69 (2) ◽

pp. 136-145

Author(s):

S. Roopa ◽

S.V. Narasimhan

Keyword(s):

Noise Control ◽

Active Noise Control ◽

Notch Filter ◽

Lms Algorithm ◽

Variable Step Size ◽

Step Size ◽

Adaptive Notch Filter ◽

Active Noise ◽

Variable Step ◽

Feedback Active Noise Control

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).

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Node Localization Based on Incremental Lms Algorithm with Variable Step Size

22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC) ◽

10.1109/cse-euc.2017.205 ◽

2017 ◽

Cited By ~ 1

Author(s):

Mou Wu ◽

Wenhua Dai ◽

Zhongyou Wang ◽

Siping Hu

Keyword(s):

Lms Algorithm ◽

Variable Step Size ◽

Node Localization ◽

Step Size ◽

Variable Step

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Application of Improved LMS Adaptive Algorithm in Acoustics Pyrometry

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.672-674.2025 ◽

2014 ◽

Vol 672-674 ◽

pp. 2025-2028

Author(s):

Shi Ping Zhang ◽

Guo Qing Shen ◽

Lian Suo An

Keyword(s):

Temperature Measurement ◽

Discrete Cosine Transform ◽

Time Delay Estimation ◽

Lms Algorithm ◽

Variable Step Size ◽

Least Mean Square ◽

Step Size ◽

Boiler Furnace ◽

Cosine Transform ◽

Variable Step

Acoustic pyrometry is a comparatively advanced method of temperature measurement developed in recent years, which possesses the essential characteristics of traditional temperature measurement approach. Considering the interferences, like strong background noise, reverberation and so on, in boiler furnace, the LMS (least mean square) adaptive filter algorithm should be improved to meet certain environment above. In order to make the LMS algorithm have the characteristic of fast convergence and small steady state error, an improved, power-normalized and variable step-size discrete cosine transform LMS algorithm is proposed, which combines the power-normalized discrete cosine transform LMS algorithm with the variable step size LMS algorithm that uses the sliding forgetting-weighted window. The time delay estimation simulation in the strong-noise environment verifies the improved DCT-MVSS LMS algorithm can achieve good performance.

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