Identification of Time Varying Systems Through Adaptive Kalman Filtering

A. Isaksson

doi:10.1016/s1474-6670(17)55517-2

Identification of Time Varying Systems Through Adaptive Kalman Filtering

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)55517-2 ◽

1987 ◽

Vol 20 (5) ◽

pp. 305-310 ◽

Cited By ~ 4

Author(s):

A. Isaksson

Keyword(s):

Kalman Filtering ◽

Time Varying ◽

Time Varying Systems

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Errata to `Comments on “Finite-Horizon Robust Kalman Filtering for Uncertain Discrete Time-Varying Systems With Uncertain-Covariance White Noises” ' [Feb 10 213-216]

IEEE Signal Processing Letters ◽

10.1109/lsp.2010.2050016 ◽

2010 ◽

Vol 17 (7) ◽

pp. 695-695 ◽

Cited By ~ 2

Author(s):

Rodrigo Fontes Souto ◽

Joo Yoshiyuki Ishihara

Keyword(s):

Discrete Time ◽

Kalman Filtering ◽

Finite Horizon ◽

Time Varying ◽

Time Varying Systems ◽

White Noises

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Finite-horizon robust Kalman filtering for uncertain discrete time-varying systems with state-delay

Asian Journal of Control ◽

10.1002/asjc.367 ◽

2011 ◽

Vol 14 (3) ◽

pp. 846-850 ◽

Cited By ~ 1

Author(s):

Zijian Liu

Keyword(s):

Discrete Time ◽

Kalman Filtering ◽

Finite Horizon ◽

Time Varying ◽

State Delay ◽

Time Varying Systems

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Deconvolution of time-varying systems by Kalman filtering: Its application to the computation of the active state in the muscle

Signal Processing ◽

10.1016/0165-1684(86)90106-4 ◽

1986 ◽

Vol 10 (3) ◽

pp. 291-301 ◽

Cited By ~ 10

Author(s):

P Rousseaux ◽

J Troquet

Keyword(s):

Kalman Filtering ◽

Active State ◽

Time Varying ◽

Time Varying Systems

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Reduced-order Kalman filtering for time-varying systems

2007 46th IEEE Conference on Decision and Control ◽

10.1109/cdc.2007.4434882 ◽

2007 ◽

Cited By ~ 4

Author(s):

J. Chandrasekar ◽

I. S. Kim ◽

D. S. Bernstein

Keyword(s):

Kalman Filtering ◽

Time Varying ◽

Reduced Order ◽

Time Varying Systems

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Improved robust finite-horizon Kalman filtering for uncertain networked time-varying systems

Information Sciences ◽

10.1016/j.ins.2014.09.017 ◽

2015 ◽

Vol 293 ◽

pp. 263-274 ◽

Cited By ~ 39

Author(s):

Hossein Rezaei ◽

Reza Mahboobi Esfanjani ◽

Mohammad Hossein Sedaaghi

Keyword(s):

Kalman Filtering ◽

Finite Horizon ◽

Time Varying ◽

Time Varying Systems

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Comments on “Finite-Horizon Robust Kalman Filtering for Uncertain Discrete Time-Varying Systems With Uncertain-Covariance White Noises”

IEEE Signal Processing Letters ◽

10.1109/lsp.2008.2005046 ◽

2010 ◽

Vol 17 (2) ◽

pp. 213-216 ◽

Cited By ~ 10

Author(s):

Rodrigo Fontes Souto ◽

JoÃo Yoshiyuki Ishihara

Keyword(s):

Discrete Time ◽

Kalman Filtering ◽

Finite Horizon ◽

Time Varying ◽

Time Varying Systems ◽

White Noises

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Finite-horizon robust Kalman filtering for uncertain discrete time-varying systems with uncertain-covariance white noises

IEEE Signal Processing Letters ◽

10.1109/lsp.2006.873148 ◽

2006 ◽

Vol 13 (8) ◽

pp. 493-496 ◽

Cited By ~ 72

Author(s):

Zhe Dong ◽

Zheng You

Keyword(s):

Discrete Time ◽

Kalman Filtering ◽

Finite Horizon ◽

Time Varying ◽

Time Varying Systems ◽

White Noises

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Maximum‐correntropy‐based Kalman filtering for time‐varying systems with randomly occurring uncertainties: An event‐triggered approach

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.5368 ◽

2020 ◽

Author(s):

Tingli Su ◽

Zidong Wang ◽

Lei Zou ◽

Fuad E. Alsaadi

Keyword(s):

Kalman Filtering ◽

Time Varying ◽

Randomly Occurring Uncertainties ◽

Time Varying Systems ◽

Event Triggered

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Stochastic Robust Kalman Filtering for Linear Time-Varying Systems with a Multiplicative Measurement Noise

IFAC Proceedings Volumes ◽

10.3182/20080706-5-kr-1001.02123 ◽

2008 ◽

Vol 41 (2) ◽

pp. 12546-12551

Author(s):

Won-Sang Ra ◽

Ick-Ho Whang

Keyword(s):

Kalman Filtering ◽

Linear Time ◽

Measurement Noise ◽

Time Varying ◽

Time Varying Systems

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Controllability of Linear Time Varying Systems: New Algebraic Criteria

1993 American Control Conference ◽

10.23919/acc.1993.4793155 ◽

1993 ◽

Author(s):

Hngo Leiva ◽

Brad Lehman

Keyword(s):

Linear Time ◽

Time Varying ◽

Time Varying Systems

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