Extracting the relevant delays in time series modelling

Cyril Goutte

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    Abstract

    In this contribution, we suggest a convenient way to use generalisation error to extract the relevant delays from a time-varying process, i.e. the delays that lead to the best prediction performance. We design a generalisation-based algorithm that takes its inspiration from traditional variable selection, and more precisely stepwise forward selection. The method is compared to other forward selection schemes, as well as to a nonparametric tests aimed at estimating the embedding dimension of time series. The final application extends these results to the efficient estimation of FIR filters on some real data
    Original languageEnglish
    Title of host publicationNeural Networks for Signal Processing VII - Proceedings of the 1997 IEEE workshop
    Place of PublicationPiscataway
    PublisherIEEE
    Publication date1997
    Pages92-101
    ISBN (Print)0-7803-4256-9
    DOIs
    Publication statusPublished - 1997
    EventNeural Networks for Signal Processing VII - Amelia Island, FL, USA
    Duration: 1 Jan 1997 → …

    Conference

    ConferenceNeural Networks for Signal Processing VII
    CityAmelia Island, FL, USA
    Period01/01/1997 → …

    Bibliographical note

    Copyright: 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

    Cite this

    Goutte, C. (1997). Extracting the relevant delays in time series modelling. In Neural Networks for Signal Processing VII - Proceedings of the 1997 IEEE workshop (pp. 92-101). IEEE. https://doi.org/10.1109/NNSP.1997.622387