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Knowledge of the noise distribution is typically crucial for the state estimation of general state-space models. However, properties of the noise process are often unknown in the majority of practical applications. The distribution of the noise may also be non-stationary or state dependent and that prevents the use of off-line tuning methods. For linear(More)
—This paper is concerned with a fixed-point implementation of the extended Kalman filter (EKF) for applications in sensorless control of ac motor drives. The sensitivity of the EKF to round-off errors is well known, and numerically advantageous implementations based on the square-root decomposition of covariance matrices have been developed to address this(More)
The use of the variational Bayes (VB) approximation in Bayesian filtering is studied, both as a means to accelerate marginalized particle filtering and as a deterministic local (one-step) approximation. The VB method of approximation is reviewed, together with restrictions that allow various computational savings to be achieved. These variants provide a(More)
The particle filter provides a general solution to the nonlinear filtering problem with arbitrarily accuracy. However, the curse of dimensionality prevents its application in cases where the state dimensionality is high. Further, estimation of stationary parameters is a known challenge in a particle filter framework. We suggest a marginalization approach(More)
An extension of the AutoRegressive (AR) model is studied, which allows transformations and distortions on the regressor to be handled. Many important signal processing problems are amenable to this Extended AR (i.e., EAR) model. It is shown that Bayesian identification and prediction of the EAR model can be performed recursively, in common with the AR model(More)
A sophisticated simulator of permanent magnet synchronous machine (PMSM) drive was developed and is used for research into model-based sensorless control strategies. In this paper, we focus on estimators based on the extended Kalman Filter (EKF). The limits and possible improvements of the EKF are investigated using the developed simulator and real data(More)
Factor Analysis (FA) is a well established method for factors separation in analysis of dynamic medical imaging. However , its assumptions are valid only in limited regions of interest (ROI) in the images which must be selected manually or using heuristics. The resulting quality of separation is sensitive to the choice of these ROI. We propose a new(More)
This paper addresses on-line early detection of inter-area electro-mechanical oscillations in power systems using dynamic data such as currents, voltages and angle differences measured across transmission lines in real time. The collected data are evaluated in real-time with the main objective to give the transmission operator qualitative information(More)