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• W2418646289 abstract "In this brief, a robust and sparse recursive adaptive filtering algorithm, called convex regularized recursive maximum correntropy (CR-RMC), is derived by adding a general convex regularization penalty term to the maximum correntropy criterion (MCC). An approximate expression for automatically selecting the regularization parameter is also introduced. Simulation results show that the CR-RMC can significantly outperform the original recursive maximum correntropy (RMC) algorithm especially when the underlying system is very sparse. Compared with the convex regularized recursive least squares (CR-RLS) algorithm, the new algorithm also shows strong robustness against impulsive noise. The CR-RMC also performs much better than other LMS-type sparse adaptive filtering algorithms based on MCC." @default.
• W2418646289 created "2016-06-24" @default.
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• W2418646289 date "2016-12-01" @default.
• W2418646289 modified "2023-10-18" @default.
• W2418646289 title "Convex regularized recursive maximum correntropy algorithm" @default.
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• W2418646289 doi "https://doi.org/10.1016/j.sigpro.2016.05.030" @default.
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