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

19 Citations (Scopus)

Abstract

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
Volume151
Issue number2
DOIs
Publication statusPublished - 2006
MoE publication typeA1 Journal article-refereed

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Wavelet Analysis

Keywords

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

Cite this

Olkkonen, Hannu ; Pesola, Peitsa ; Olkkonen, Juuso ; Zhou, Hui. / Hilbert transform assisted complex wavelet transform for neuroelectric signal analysis. In: Journal of Neuroscience Methods. 2006 ; Vol. 151, No. 2. pp. 106-113.
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Hilbert transform assisted complex wavelet transform for neuroelectric signal analysis. / Olkkonen, Hannu (Corresponding Author); Pesola, Peitsa; Olkkonen, Juuso; Zhou, Hui.

In: Journal of Neuroscience Methods, Vol. 151, No. 2, 2006, p. 106-113.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Hilbert transform assisted complex wavelet transform for neuroelectric signal analysis

AU - Olkkonen, Hannu

AU - Pesola, Peitsa

AU - Olkkonen, Juuso

AU - Zhou, Hui

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N2 - 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.

AB - 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.

KW - complex wavelet transform

KW - analytic signal

KW - Hilbert transform

KW - shift invariance

KW - phase distortion

KW - neuroelectric signals

KW - wavelet transforms

U2 - 10.1016/j.jneumeth.2005.06.028

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