Exponential stability in discrete-time filtering for non-ergodic signals

被引:34
作者
Budhiraja, A [1 ]
Ocone, D
机构
[1] Univ Notre Dame, Dept Math, Notre Dame, IN 46656 USA
[2] Rutgers State Univ, Dept Math, New Brunswick, NJ 08854 USA
关键词
nonlinear filtering; asymptotic stability; measure valued processes;
D O I
10.1016/S0304-4149(99)00032-0
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper we prove exponential asymptotic stability for discrete-time filters for signals arising as solutions of d-dimensional stochastic difference equations. The observation process is the signal corrupted by an additive white noise of sufficiently small variance. The model for the signal admits non-ergodic processes. We show that almost surely, the total variation distance between the optimal filter and an incorrectly initialized filter converges to 0 exponentially fast as time approaches infinity. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:245 / 257
页数:13
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