Stabilization of a Bias-Compensated Normalized Least-Mean-Square Algorithm for Noisy Inputs

@article{Jung2017StabilizationOA,
  title={Stabilization of a Bias-Compensated Normalized Least-Mean-Square Algorithm for Noisy Inputs},
  author={Sang Mok Jung and Poogyeon Park},
  journal={IEEE Transactions on Signal Processing},
  year={2017},
  volume={65},
  pages={2949-2961}
}
This paper proposes a stability-guaranteed bias-compensated normalized least-mean-square (BC-NLMS) algorithm for noisy inputs. The bias-compensated algorithms require the estimated input noise variance in the elimination process of the bias caused by noisy inputs. However, the conventional methods of estimating the input noise variance in those algorithms might cause the instability for a specific situation. This paper first analyzes the stability of the BC-NLMS algorithm by investigating the… CONTINUE READING
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