# On the Phase Portrait of the Fast Filtering Algorithms

ESAIM: Control, Optimisation and Calculus of Variations (2010)

- Volume: 4, page 609-630
- ISSN: 1292-8119

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topZhou, Yishao. "On the Phase Portrait of the Fast Filtering Algorithms." ESAIM: Control, Optimisation and Calculus of Variations 4 (2010): 609-630. <http://eudml.org/doc/197372>.

@article{Zhou2010,

abstract = {
Fast filtering algorithms arising from linear filtering and
estimation are nonlinear dynamical systems whose initial values
are the statistics of the observation process. In this paper, we
give a fairly complete description of the phase portrait for such
nonlinear dynamical systems, as well as a special type of naturally
related matrix Riccati equation.
},

author = {Zhou, Yishao},

journal = {ESAIM: Control, Optimisation and Calculus of Variations},

keywords = {Fast filtering algorithms; Riccati equations; Kalman
filtering; nonlinear dynamical systems.; Kalman filtering; fast filtering algorithms; nonlinear dynamical systems; positivity conditions},

language = {eng},

month = {3},

pages = {609-630},

publisher = {EDP Sciences},

title = {On the Phase Portrait of the Fast Filtering Algorithms},

url = {http://eudml.org/doc/197372},

volume = {4},

year = {2010},

}

TY - JOUR

AU - Zhou, Yishao

TI - On the Phase Portrait of the Fast Filtering Algorithms

JO - ESAIM: Control, Optimisation and Calculus of Variations

DA - 2010/3//

PB - EDP Sciences

VL - 4

SP - 609

EP - 630

AB -
Fast filtering algorithms arising from linear filtering and
estimation are nonlinear dynamical systems whose initial values
are the statistics of the observation process. In this paper, we
give a fairly complete description of the phase portrait for such
nonlinear dynamical systems, as well as a special type of naturally
related matrix Riccati equation.

LA - eng

KW - Fast filtering algorithms; Riccati equations; Kalman
filtering; nonlinear dynamical systems.; Kalman filtering; fast filtering algorithms; nonlinear dynamical systems; positivity conditions

UR - http://eudml.org/doc/197372

ER -

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