Invariant measures of the pair: state, approximate filtering process
Ł. Stettner (1991)
Colloquium Mathematicae
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Displaying similar documents to “On a role of predictor in the filtering stability.”
Invariant measures of the pair: state, approximate filtering process
A note on the diffusive scaling limit for a class of linear systems.
Nagahata, Yukio, Yoshida, Nobuo (2010)
Electronic Communications in Probability [electronic only]
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Robust mixing.
Ganapathy, Murali (2007)
Electronic Journal of Probability [electronic only]
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General state space Markov chains and MCMC algorithms.
Roberts, Gareth O., Rosenthal, Jeffrey S. (2004)
Probability Surveys [electronic only]
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Strong hydrodynamic limit for attractive particle systems on .
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Electronic Journal of Probability [electronic only]
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A note on bisexual Galton-Watson branching processes with immigration.
M. González, M. Molina, M. Mota (2001)
Extracta Mathematicae
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A coupling technique for stochastic comparison of functions of Markov processes.
Doisy, M. (2000)
Journal of Applied Mathematics and Decision Sciences
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On the core property of the cylinder functions class in the construction of interacting particle systems
Anja Voss-Böhme (2011)
Kybernetika
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For general interacting particle systems in the sense of Liggett, it is proven that the class of cylinder functions forms a core for the associated Markov generator. It is argued that this result cannot be concluded by straightforwardly generalizing the standard proof technique that is applied when constructing interacting particle systems from their Markov pregenerators.
Generic properties of iterated function systems with place dependent probabilities.
Bielaczyc, Tomasz (2006)
Zeszyty Naukowe Uniwersytetu Jagiellońskiego. Universitatis Iagellonicae Acta Mathematica
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Dynamical systems with multiplicative perturbations: the strong convergence of measures
Katarzyna Horbacz (1993)
Annales Polonici Mathematici
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We give sufficient conditions for the strong asymptotic stability of the distributions of dynamical systems with multiplicative perturbations. We apply our results to iterated function systems.