Schack B, Bareshova E, Grieszbach G, Witte H
Institute of Medical Statistics, Informatics and Documentation, Medical Facility, Friedrich Schiller University of Jena, Germany.
Med Biol Eng Comput. 1995 May;33(3 Spec No):492-8. doi: 10.1007/BF02510536.
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.
由于生物信号常常具有非平稳特性，因此在频谱域中采用动态方法来分析生物信号是必要的。本文提出了一种将时变自回归滑动平均（ARMA）模型拟合到非平稳信号的自适应过程，该过程适用于在线计算。研究了模型参数估计的性质，并在平稳情况下与收敛估计方法的结果进行了比较。在此基础上，计算了具有高时间和频谱分辨率的时变频谱参数，并展示了它们在脑电图分析和激光多普勒血流测量中的应用可能性。
