Ergodicity and mixing conditions of Markov processes in nonparametric filtering problems (Q1180934)
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scientific article; zbMATH DE number 30233
| Language | Label | Description | Also known as |
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| English | Ergodicity and mixing conditions of Markov processes in nonparametric filtering problems |
scientific article; zbMATH DE number 30233 |
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Ergodicity and mixing conditions of Markov processes in nonparametric filtering problems (English)
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27 June 1992
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The problem of filtering a discrete-time Markov process is considered in the case where the law of the state process is unknown; only the dependence between the state and the observation are known. The authors study ergodicity and strong mixing conditions for the system. Then, by applying a classical nonparametric estimator for the density, they can deduce nonparametric filters which are asymptotically optimal.
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discrete-time Markov process
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ergodicity
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strong mixing conditions
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nonparametric estimator
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nonparametric filters
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