title: Time-frequency filtering of MEG signals with matching pursuit.
abstract: Time-frequency signal analysis based on various decomposition techniques is widely used in biomedical applications. Matching Pursuit is a new adaptive approach for time-frequency decomposition of such biomedical signals. Its advantage is that it creates a concise signal approximation with the help of a small set of Gabor atoms chosen iteratively from a large and redundant set. In this paper, the usage of Matching Pursuit for time-frequency filtering of biomagnetic signals is proposed. The technique was validated on artificial signals and its performance was tested for varying signal-to-noise ratios using both simulated and real MEG somatic evoked magnetic field data.
authors.affiliation: Biomagnetic Center, Department of Neurology, Friedrich Schiller University Jena, Erlanger Allee 101, 07747 Jena, Germany. maciekg@biomag.uni-jena.de
authors.forename: Maciej
authors.initials: M
authors.lastname: Gratkowski
authors.forename: Jens
authors.initials: J
authors.lastname: Haueisen
authors.forename: Lars
authors.initials: L
authors.lastname: Arendt-Nielsen
authors.forename: Andrew C N
authors.initials: AC
authors.lastname: Chen
authors.forename: Frank
authors.initials: F
authors.lastname: Zanow
mesh_terms: D000465:Algorithms; D005073:Evoked Potentials, Somatosensory / Q000502:physiology; D005583:Fourier Analysis; D006801:Humans; D015225:Magnetoencephalography / Q000706:statistics & numerical data*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors