Hilbert transform assisted complex wavelet transform for neuroelectric signal analysis

Hannu Olkkonen (Corresponding Author), Peitsa Pesola, Juuso Olkkonen, Hui Zhou

    Research output: Contribution to journalArticleScientificpeer-review

    21 Citations (Scopus)


    In this work, we present a new approach for shift invariant complex wavelet analysis of neuroelectric signals. A key idea is to preprocess the signal with the Hilbert transformer to yield an analytic signal, which is then wavelet transformed using the linear phase complex scaling and wavelet filters. In different scales, the total energy of the wavelet transform coefficients is shift invariant. The decimated analytic wavelet coefficients suffer no aliasing effects, which are predominant in conventional wavelet analysis. We show the usefulness of the present method in multi-scale analysis of the neuroelectric signal waveforms.
    Original languageEnglish
    Pages (from-to)106-113
    Number of pages8
    JournalJournal of Neuroscience Methods
    Issue number2
    Publication statusPublished - 2006
    MoE publication typeA1 Journal article-refereed


    • complex wavelet transform
    • analytic signal
    • Hilbert transform
    • shift invariance
    • phase distortion
    • neuroelectric signals
    • wavelet transforms


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