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- Jan Stecha
- Automatica
- 1996

- Milos Fink, Jan Stecha
- Kybernetika
- 1971

- Jirka Roubal, Petr Husek, Jan Stecha
- IEEE Trans. Education
- 2010

Real time system parameter estimation from the set of input-output data is usually solved by the quadratic norm minimization of system equations errors known as least squares (LS). But measurement errors are also in the data matrix and so it is necessary to use a modification known as total least squares (TLS) or mixed LS and TLS. Instead of quadratic norm… (More)

- Jan Stecha, Vladimir Havlena
- Modelling, Identification and Control
- 2003

The paper presents LQ/LQG optimal controller based on a set of parallel models with given probabilities of individual models (mixture distribution). Both state feedback LQ controller (in case of measurable state) and output feedback LQG controller are described. Copyright c © 2002 IFAC.

- Jan Stecha
- 2007

This paper presents experiments with tracking time{varying parameters of a dynamic system applied to parameter estimation and smoothing of piecewise continuous function. The smoothing algorithm is based on bayesian computation of the probability distribution over the set of alternative hypotheses describing a set of alternative models of expected (possible)… (More)

Stability is the first demand of the feedback control design. The parametrization of all stabilizing controllers is standard theory. The stabilizing controller has some free parameters which can be used for further optimization. Linear Quadratic (LQ) control and Dead Beat control are standard algorithms for optimal control of discrete time models of real… (More)

- Tomas Vitek, Daniel Pachner, Jan Stecha
- 2007 IEEE International Conference on Control…
- 2007

Effective management practices in the tourism and hotel area have seldom been more important than at the present time. Pricing decisions cannot be taken without serious thought. The key idea is to formulate a pricing strategy of a provider as a sequential decision problem, which can be transformed into an optimal control problem. The yield management can… (More)

- J. Stecha, V. Havlena
- 2012 15th International Conference on Information…
- 2012

Kalman filter is a frequently used tool for linear state estimation due to its simplicity and optimality. It can further be used for fusion of information obtained from multiple sensors. Kalman filtering is also often applied to nonlinear systems. As the direct application of bayesian functional recursion is computationally not feasible, approaches commonly… (More)