Variable Step-Size LMS Algorithm With a Gradient-Based Weighted Average

IEEE Signal Processing Letters（2009）

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摘要

This paper proposes a new variable step-size least-mean-square (VSLMS) algorithm with an approach in which a gradient-based weighted average is used to improve the weakness of previous VSLMS for application to unknown channel estimation or system identification in low-SNR or colored input environments. The proposed scheme leads to a faster convergence rate and a lower misadjustment error.

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关键词

Least squares approximation,Convergence,Finite impulse response filter,Signal processing algorithms,Adaptive filters,Channel estimation,Error correction,Noise reduction,Noise measurement,Colored noise

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