Methods of dynamic spectral analysis by self-exciting autoregressive moving average models and their application to analysing biosignals.

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.