Decomposition algorithms for analysing brain signals

Klaus Muller, J. Kohlmorgen, A. Ziehe, B. Blankertz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Analyzing biomedical data-e.g. from the brain-we encounter fundamental problems that lie largely in the fields of signal processing and machine learning. The current paper presents at first a method to deal with non-stationary signals, subsequently the signal processing technique of independent component analysis (ICA) is reviewed. We use EEG recordings of continuous auditory perception as illustration for the discussed algorithms.

Original languageEnglish
Title of host publicationIEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages105-110
Number of pages6
ISBN (Print)0780358007, 9780780358003
DOIs
Publication statusPublished - 2000
Externally publishedYes
EventIEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000 - Lake Louise, Canada
Duration: 2000 Oct 12000 Oct 4

Other

OtherIEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
CountryCanada
CityLake Louise
Period00/10/100/10/4

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Control and Systems Engineering

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  • Cite this

    Muller, K., Kohlmorgen, J., Ziehe, A., & Blankertz, B. (2000). Decomposition algorithms for analysing brain signals. In IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000 (pp. 105-110). [882455] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASSPCC.2000.882455