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This paper proposes new recursive fixed-point smoother and filter using covariance information in linear continuous-time stochastic systems. To be able to treat the stochastic signal estimation problem, a performance criterion, extended from the criterion in the *H*_{} filtering problem by introducing the stochastic expectation, is newly introduced in this paper. The criterion is transformed equivalently into a min-max principle in game theory, and an observation equation in the Krein spaces is obtained as a result. For γ^{2}<

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.9 pp.2261-2271

- Publication Date
- 2001/09/01

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- PAPER

- Category
- Systems and Control

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Seiichi NAKAMORI, "Design of Linear Continuous-Time Stochastic Estimators Using Covariance Information in Krein Spaces" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 9, pp. 2261-2271, September 2001, doi: .

Abstract: This paper proposes new recursive fixed-point smoother and filter using covariance information in linear continuous-time stochastic systems. To be able to treat the stochastic signal estimation problem, a performance criterion, extended from the criterion in the *H*_{} filtering problem by introducing the stochastic expectation, is newly introduced in this paper. The criterion is transformed equivalently into a min-max principle in game theory, and an observation equation in the Krein spaces is obtained as a result. For γ^{2}<

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_9_2261/_p

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@ARTICLE{e84-a_9_2261,

author={Seiichi NAKAMORI, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={Design of Linear Continuous-Time Stochastic Estimators Using Covariance Information in Krein Spaces},

year={2001},

volume={E84-A},

number={9},

pages={2261-2271},

abstract={This paper proposes new recursive fixed-point smoother and filter using covariance information in linear continuous-time stochastic systems. To be able to treat the stochastic signal estimation problem, a performance criterion, extended from the criterion in the *H*_{} filtering problem by introducing the stochastic expectation, is newly introduced in this paper. The criterion is transformed equivalently into a min-max principle in game theory, and an observation equation in the Krein spaces is obtained as a result. For γ^{2}<

keywords={},

doi={},

ISSN={},

month={September},}

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TY - JOUR

TI - Design of Linear Continuous-Time Stochastic Estimators Using Covariance Information in Krein Spaces

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 2261

EP - 2271

AU - Seiichi NAKAMORI

PY - 2001

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E84-A

IS - 9

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - September 2001

AB - This paper proposes new recursive fixed-point smoother and filter using covariance information in linear continuous-time stochastic systems. To be able to treat the stochastic signal estimation problem, a performance criterion, extended from the criterion in the *H*_{} filtering problem by introducing the stochastic expectation, is newly introduced in this paper. The criterion is transformed equivalently into a min-max principle in game theory, and an observation equation in the Krein spaces is obtained as a result. For γ^{2}<

ER -