The classical approach to designing lters for systems where system equations are linear and measurement equations are nonlinear is to linearise measurement equations, and apply an Extended Kalman Filter (EKF). This results in suboptimal, biased, and often divergent lters. Many schemes proposed to improve the performance of the EKF concentrated on better linearisation techniques, iterative techn...

This paper provides a unified view of, and a further insight into, a class of optimal reduced-rank estimators and filters. An alternating power (AP) method for computing the optimal reduced-rank estimators and filters is derived and analyzed. The AP method is a generalization of the conventional power method for subspace computation, which is shown to be globally and exponentially convergent un...

Quantum mechanical systems exhibit an inherently probabilistic nature upon measurement. Using a quantum noise model to describe the stochastic evolution of the open quantum system and working in parallel with classical indeterministic control theory, we present the theory of nonlinear optimal quantum feedback control. The resulting quantum Bellman equation is then applied to the explicitly solv...

In this paper we show that the knowledge of noise statistics contaminating a signal can be effectively used to choose an optimal Gaussian filter to eliminate noise. Very specifically, we show that the additive white Gaussian noise (AWGN) contaminating a signal can be filtered best by using a Gaussian filter of specific characteristics. The design of the Gaussian filter bears relationship with t...

The application of a (smoothing) filter is common practice in applications where time series are involved. The literature on time series similarity measures, however, seems to completely ignore the possibility of applying a filter first. In this paper, we investigate to what extent the benefit obtained by more complex distance measures may be achieved by simply applying a filter to the original...

In this paper novel compression techniques are developed for portable heart-monitoring equipment that could also form the basis for more intelligent diagnostic systems thanks to the way the compression algorithms depend on signal classification. There are two main categories of compression which are employed for electrocardiogram signals: lossless and lossy. Design of an optimal Wiener filter i...

motion analysis and quality assessment of human sperm cell is of great importance for clinical applications of male infertility. sperm tracking is quite complex due to cell collision, occlusion and missed detection. the goal of this study is simultaneous tracking of multiple human sperm cells. in the first step in this research the frame difference algorithm is used for background subtraction. ...

The signal-to-noise ratio maximizing approach in optimal filtering provides a robust tool to detect signals in the presence of colored noise. The method fails, however, when the data present a regimelike behavior. An approach is developed in this manuscript to recover local (in phase space) behavior in an intermittent regimelike behaving system. The method is first formulated in its general for...

The classical approach to system identification is based on stochastic assumptions about the measurement error, and provides estimates that have random nature. Worst-case identification, on the other hand, only assumes the knowledge of deterministic error bounds, and establishes guaranteed estimates, thus being in principle better suited for the use in control design. However, a main limitation...