Abstract
We introduce a modified algorithm to perform nonlinear filtering of a time series by locally linear phase space projections. Unlike previous implementations, the algorithm can be used not only for a posteriori processing but also includes the possibility to perform real-time filtering in a data stream. Apart from making the filter causal by restricting neighbor searches to the past, the data base that represents the phase space structure generated by the data is updated dynamically. This also allows filtering of nonstationary signals and dynamic parameter adjustment. We discuss exemplary applications, including the real-time extraction of the fetal electrocardiogram from abdominal recordings.
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