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W1557920377 abstract "We propose a modified leaky-LMS filter that ensures stability of the estimates w(k) in the presence of bounded noise, without introducing any bias term and with the added cost of only a comparison and a multiplication per iteration when compared to the classical LMS algorithm. The new algorithm is further shown to converge for l/sub p/ noise and persistently exciting regressors. It also provides bounded estimates even in finite precision arithmetic. The stability and convergence properties of the new algorithm are established through a deterministic analysis that is based on the Lyapunov theory for the stability of nonlinear difference equations." @default.
W1557920377 created "2016-06-24" @default.
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W1557920377 date "2002-12-24" @default.
W1557920377 modified "2023-09-22" @default.
W1557920377 title "An unbiased and cost-effective leaky-LMS filter" @default.
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W1557920377 doi "https://doi.org/10.1109/acssc.1996.599109" @default.
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