2003/04/30 by Pavel Chigansky, Robert Liptser
Mathematics · #math.PR #msc:93E11 #msc:60J57
paper · pdf · doi:10.1214/105051604000000873
published as Annals of Applied Probability 2004, Vol. 14, No. 4, 2038-2056 · Published at http://dx.doi.org/10.1214/105051604000000873 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
arxiv created 2005/04/06 · arxiv updated 2009/11/30
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.