Stability of nonlinear filters in nonmixing case

Pavel Chigansky*, Robert Liptser

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The nonlinear filtering equation is said to be stable if it "forgets" the initial condition. It is known that the filter might be unstable even if the signal is an ergodic Markov chain. In general, the filtering stability requires stronger signal ergodicity provided by the, so called, mixing condition. The latter is formulated in terms of the transition probability density of the signal. The most restrictive requirement of the mixing condition is the uniform positiveness of this density. We show that it might be relaxed regardless of an observation process structure.

Original languageAmerican English
Pages (from-to)2038-2056
Number of pages19
JournalAnnals of Applied Probability
Volume14
Issue number4
DOIs
StatePublished - Nov 2004
Externally publishedYes

Keywords

  • Filtering stability
  • Geometric ergodicity

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