English

Duality for Nonlinear Filtering I: Observability

Optimization and Control 2022-08-16 v1 Probability

Abstract

This paper 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 (BSDE) 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 formulae, 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).

Keywords

Cite

@article{arxiv.2208.06586,
  title  = {Duality for Nonlinear Filtering I: Observability},
  author = {Jin Won Kim and Prashant G. Mehta},
  journal= {arXiv preprint arXiv:2208.06586},
  year   = {2022}
}

Comments

arXiv admin note: text overlap with arXiv:2207.07709

R2 v1 2026-06-25T01:40:55.753Z