A kernel-based RLS algorithm for nonlinear adaptive filtering using sparse approximation theory

Abstract

In the last ten years, there has been an explosion of activity in the field of learning algorithms utilizing reproducing kernels, most notably for classification and regression. A common characteristic in kernelbased methods is that they deal with models whose order equals the number of input data, making them unsuitable for online applications. In this… (More)

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