Title
Weiss–Weinstein Lower Bounds for Markovian Systems. Part 1: Theory
Abstract
Being essentially free from regularity conditions, the Weiss-Weinstein estimation error lower bound can be applied to a larger class of systems than the well-known Crameacuter-Rao lower bound. Thus, this bound is of special interest in applications involving hybrid systems, i.e., systems with both continuously and discretely distributed parameters, which can represent, in practice, fault-prone systems. However, the requirement to know explicitly the joint distribution of the estimated parameters with all the measurements makes the application of the Weiss-Weinstein lower bound to Markovian dynamic systems cumbersome. A sequential algorithm for the computation of the Crameacuter-Rao lower bound for such systems has been recently reported in the literature. Along with the marginal state distribution, the algorithm makes use of the transitional distribution of the Markovian state process and the distribution of the measurements at each time step conditioned on the appropriate states, both easily obtainable from the system equations. A similar technique is employed herein to develop sequential Weiss-Weinstein lower bounds for a class of Markovian dynamic systems. In particular, it is shown that in systems satisfying the Crameacuter-Rao lower bound regularity conditions, the sequential Weiss-Weinstein lower bound derived herein reduces, for a judicious choice of its parameters, to the sequential Crameacuter-Rao lower bound
Year
DOI
Venue
2007
10.1109/TSP.2007.893208
IEEE Transactions on Signal Processing
Keywords
Field
DocType
Markov processes,signal processing,Cramer-Rao lower bound,Markovian dynamic systems,Markovian state process,Weiss-Weinstein estimation error lower bound,marginal state distribution,Dynamic Markovian systems,estimation error lower bound
Cramér–Rao bound,Chapman–Robbins bound,Mathematical optimization,Joint probability distribution,Upper and lower bounds,Distributed parameter system,Sequential algorithm,Hybrid system,Mathematics,Marginal distribution
Journal
Volume
Issue
ISSN
55
5
1053-587X
Citations 
PageRank 
References 
6
0.54
9
Authors
2
Name
Order
Citations
PageRank
I. Rapoport1182.09
Y. Oshman2152.75