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Duality for Nonlinear Filtering I: Observability

delete2024-02-01
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OA
AI
J
Jin Won Kim
P
Prashant G. Mehta *
DOI:10.1109/TAC.2023.3279206delete
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摘要

摘要

En 中文
This article is concerned with the development and use of duality theory for a hidden Markov model (HMM) with white noise observations. The main contribution of this work is to introduce a backward stochastic differential equation as a dual control system. A key outcome is that stochastic observability (resp. detectability) of the HMM is expressed in dual terms: as controllability (resp. stabilizability) of the dual control system. All aspects of controllability, namely, definition of controllable space and controllability gramian, along with their properties and explicit formulas, are discussed. The proposed duality is shown to be an exact extension of the classical duality in linear systems theory. One can then relate and compare the linear and the nonlinear systems. A side-by-side summary of this relationship is given in a tabular form (Table II).
Keyword:
Hidden Markov models
Observability
Stochastic processes
Controllability
Stability analysis
Filtering
Asymptotic stability
Nonlinear filtering
observability
stochastic systems

期刊

IEEE Transactions on Automatic Control 封面图
IEEE Transactions on Automatic Control
IF:
7
论文数:
1.3W
被引数:
6.7W

机构

U
University of Potsdam
学者数:
7.8K
论文数: 7.1K
被引数: 1.4W
University of Illinois System 封面图
University of Illinois System
学者数:
6.8W
论文数: 6.2W
被引数: 644
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