The problem to track time-varying properties of a signal is studied. The somewhat contradictory notion of \time-varying spectrum" and how to estimate the \current" spectrum in an on-line fashion is discussed. The traditional concepts and relations between time and frequency resolution are crucial for this problem. An adaptive estimation algorithm is used to estimate the parameters of a time-var...

Modeling heartbeat variability remains a challenging signal-processing goal in the presence of highly non-stationary cardiovascular control dynamics. We propose a novel differential autoregressive modeling approach within a point process probability framework for analyzing R-R interval and blood pressure variations. We apply the proposed model to both synthetic and experimental heartbeat interv...

In this paper we study optimal control of time-varying multi-input multi-output stochastic systems and develop a generalised minimum variance controller. The system to be controlled is described using a multiinput multi-output time-varying autoregressive moving average model that has multiple delays between the output and input. The controller minimises the sum of output tracking error variance...

R A I N E R DA H L H AU S , 1 M I C H A E L H . N E U M A N N 2 and RAINER VON SACHS 3 Institut fuÈ r Angewandte Mathematik, UniversitaÈ t Heidelberg, Im Neuenheimer Feld 294, D-69120 Heidelberg, Germany. E-mail: [email protected] SFB 373, Humboldt-UniversitaÈ t zu Berlin, Spandauer Strasse 1, D-10178 Berlin, Germany. E-mail: [email protected] Institut de Statistique, U...

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Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution...

Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution...

| The problem to track time-varying properties of a signal is studied. The somewhat contradictory notion of \time-varying spectrum" and how to estimate the \current" spectrum in an on-line fashion is discussed. The traditional concepts and relations between time and frequency resolution are crucial for this problem. We introduce two deenitions for the time resolution of lters, essentially measu...

The problem to track time-varying properties of a signal is studied. The somewhat contradictory notion of \time-varying spectrum" and how to estimate the \current" spectrum in an on-line fashion is discussed. The traditional concepts and relations between time-and frequency resolution are crucial for this problem. As adaptive estimation algorithm is used to estimate the parameters of a time-var...