Lancaster EPrints

Estimating time-evolving partial coherence between signals via multivariate locally stationary wavelet processes

Park, Timothy Alexander and Eckley, Idris and Ombao, Hernando (2014) Estimating time-evolving partial coherence between signals via multivariate locally stationary wavelet processes. IEEE Transactions on Signal Processing, 62 (20). 5240 - 5250. ISSN 1053-587X

[img]
Preview
PDF (ParkEckleyOmbao2014) - Submitted Version
Download (868Kb) | Preview

    Abstract

    We consider the problem of estimating time-localized cross-dependence in a collection of nonstationary signals. To this end, we develop the multivariate locally stationary wavelet framework, which provides a time-scale decomposition of the signals and, thus, naturally captures the time-evolving scale-specific cross-dependence between components of the signals. Under the proposed model, we rigorously define and estimate two forms of cross-dependence measures: wavelet coherence and wavelet partial coherence. These dependence measures differ in a subtle but important way. The former is a broad measure of dependence, which may include indirect associations, i.e., dependence between a pair of signals that is driven by another signal. Conversely, wavelet partial coherence measures direct linear association between a pair of signals, i.e., it removes the linear effect of other observed signals. Our time-scale wavelet partial coherence estimation scheme thus provides a mechanism for identifying hidden dynamic relationships within a network of nonstationary signals, as we demonstrate on electroencephalograms recorded in a visual–motor experiment.

    Item Type: Article
    Journal or Publication Title: IEEE Transactions on Signal Processing
    Additional Information: c 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.
    Subjects:
    Departments: Faculty of Science and Technology > Mathematics and Statistics
    ID Code: 70987
    Deposited By: ep_importer_pure
    Deposited On: 26 Sep 2014 09:14
    Refereed?: Yes
    Published?: Published
    Last Modified: 23 Oct 2017 04:03
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/70987

    Actions (login required)

    View Item