摘要: In this contribution, we suggest a convenient way to use generalisation error extract the relevant delays from time-varying process, i.e. that lead best prediction performance. We design generalisation-based algorithm takes its inspiration traditional variable selection, and more precisely stepwise forward selection. The method is compared other selection schemes, as well nonparametric tests aimed at estimating embedding dimension of time series. final application extends these results efficient estimation FIR filters on some real data.
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