title: Methods of dynamic spectral analysis by self-exciting autoregressive moving average models and their application to analysing biosignals.
abstract: Dynamic methods in the spectral domain are necessary to analyse biological signals because of the frequently nonstationary character of the signals. The paper presents an adaptive procedure of fitting time-dependent ARMA models to nonstationary signals, which is suitable for on-line calculations. The properties of the model parameter estimations are examined, and in the stationary case are compared with the results of convergent estimation methods. On this basis time-varying spectral parameters with high temporal and spectral resolution are calculated, and the possibility of their application is shown in EEG analysis and laser-Doppler-flowmetry.
authors.affiliation: Institute of Medical Statistics, Informatics and Documentation, Medical Facility, Friedrich Schiller University of Jena, Germany.
authors.forename: B
authors.initials: B
authors.lastname: Schack
authors.forename: E
authors.initials: E
authors.lastname: Bareshova
authors.forename: G
authors.initials: G
authors.lastname: Grieszbach
authors.forename: H
authors.initials: H
authors.lastname: Witte
mesh_terms: D004569:Electroencephalography; D005434:Flow Cytometry; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008433:Mathematics; D008954:Models, Biological