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A new set-membership filtering method, adaptive set-membership normalized least mean squares (ASM-NLMS), is presented that introduces a forgetting factor into the conventional set-membership normalized least mean squares (SM-NLMS) method. The proposed ASM-NLMS method is more effective in dealing with non-stationary systems compared to the SM-NLMS method. The performance of the proposed ASM-NLMS method...
Correntropy has been recently defined as a localised similarity measure between two random variables, exploiting higher order moments of the data. This paper presents the use of correntropy as a cost function for minimizing the error between the desired signal and the output of an adaptive filter, in order to train the filter weights.We have shown that this cost function has the computational simplicity...
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