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• W2761627596 abstract "In this paper, a novel adaptive filter algorithm, called boxed-constraint least mean square (BXCLMS) algorithm, is proposed for identifying the boxed-constrained system where the parameter to estimate is limited in a range from lower bound to upper bound. The proposed algorithm is derived by using the Karush-Kuhn-Tucker (KKT) conditions and fixed-point iteration algorithm. In addition, the stochastic behavior analysis of proposed algorithm is performed in terms of mean and mean square performance. Finally, simulations are carried out to demonstrate the performance of BXCLMS algorithm and verify the correctness of the analytical results." @default.
• W2761627596 created "2017-10-20" @default.
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• W2761627596 date "2018-03-01" @default.
• W2761627596 modified "2023-10-16" @default.
• W2761627596 title "Boxed-constraint least mean square algorithm and its performance analysis" @default.
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• W2761627596 doi "https://doi.org/10.1016/j.sigpro.2017.10.006" @default.
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