Analysis on extended kernel recursive least squares algorithm

In this paper, the extended kernel recursive least squares (Ex-KRLS) algorithm is reviewed and analyzed. We point out that the Theorem 1 in [10] is not always correct for general cases. Furthermore, the Ex-KRLS algorithm for tracking model is just a random walk KRLS algorithm. Finally, this algorithm is explained as a special Kalman filter in the reproducing kernel Hilbert space.

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