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The bias-compensated set-membership normalised LMS (BCSMNLMS) algorithm isproposed based on the concept of set-membership filtering, which incorporatesthe bias-compensation technique to mitigate the negative effect of noisyinputs. Moreover, an efficient regression noise variance estimation method isdeveloped by taking the iterative-shrinkage method. Simulations in the contextof system identification demonstrate that the misalignment of the proposedBCSM-NLMS algorithm is low for noisy inputs.

Set-membership NLMS algorithm based on bias-compensated and regression noise variance estimation for noisy inputs