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- Wemerson D. Parreira, José Carlos M. Bermudez, Cédric Richard, Jean-Yves Tourneret
- IEEE Transactions on Signal Processing
- 2011

The kernel least-mean-square (KLMS) algorithm is a popular algorithm in nonlinear adaptive filtering due to its simplicity and robustness. In kernel adaptive filters, the statistics of the input to the linear filter depends on the parameters of the kernel employed. Moreover, practical implementations require a finite nonlinearity model order. A Gaussian… (More)

- Wemerson D. Parreira, José Carlos M. Bermudez, Cédric Richard, Jean-Yves Tourneret
- 2011 19th European Signal Processing Conference
- 2011

The Kernel Least Mean Square (KLMS) algorithm is a popular algorithm in nonlinear adaptive filtering due to its simplicity and robustness. In kernel adaptive filters, the statistics of the input to the linear filter depends on the parameters of the kernel employed. A Gaussian KLMS has two design parameters; the step size and the kernel bandwidth. Thus, its… (More)

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