H-infinity parameter estimation for state-space models

Proceedings of the 2004 American Control Conference ◽

10.23919/acc.2004.1383896 ◽

2004 ◽

Cited By ~ 2

Author(s):

K. Kiriakidis ◽

R.T. O'Brien

Keyword(s):

Parameter Estimation ◽

State Space ◽

State Space Models ◽

H Infinity

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Parameter Estimation Using a Modified Version of SPSA Algorithm Applied to State Space Models

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.129.1187 ◽

2009 ◽

Vol 129 (12) ◽

pp. 1187-1194 ◽

Cited By ~ 1

Author(s):

Jorge Ivan Medina Martinez ◽

Kazushi Nakano ◽

Kohji Higuchi

Keyword(s):

Parameter Estimation ◽

State Space ◽

State Space Models

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Parameter estimation of state space models by recurrent neural networks

IEE Proceedings - Control Theory and Applications ◽

10.1049/ip-cta:19951733 ◽

1995 ◽

Vol 142 (2) ◽

pp. 114-118 ◽

Cited By ~ 16

Author(s):

J.R. Raol

Keyword(s):

Neural Networks ◽

Parameter Estimation ◽

State Space ◽

Recurrent Neural Networks ◽

State Space Models

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Sensitivity models for nonlinear filters with application to recursive parameter estimation for nonlinear state-space models

IEE Proceedings - Control Theory and Applications ◽

10.1049/ip-cta:20010235 ◽

2001 ◽

Vol 148 (2) ◽

pp. 137-145 ◽

Cited By ~ 9

Author(s):

C. Bohn ◽

H. Unbehauen

Keyword(s):

Parameter Estimation ◽

State Space ◽

Nonlinear Filters ◽

State Space Models ◽

Recursive Parameter Estimation ◽

Nonlinear State Space Models ◽

Nonlinear State

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Convolution particle filtering for parameter estimation in general state-space models

Proceedings of the 45th IEEE Conference on Decision and Control ◽

10.1109/cdc.2006.376751 ◽

2006 ◽

Cited By ~ 4

Author(s):

Fabien Campillo ◽

Vivien Rossi

Keyword(s):

Parameter Estimation ◽

State Space ◽

Particle Filtering ◽

State Space Models ◽

General State ◽

General State Space

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On-Line Parameter Estimation in General State-Space Models

Proceedings of the 44th IEEE Conference on Decision and Control ◽

10.1109/cdc.2005.1582177 ◽

2006 ◽

Cited By ~ 26

Author(s):

C. Andrieu ◽

A. Doucet ◽

V.B. Tadic

Keyword(s):

Parameter Estimation ◽

State Space ◽

State Space Models ◽

General State ◽

Line Parameter ◽

On Line ◽

General State Space

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A scenario-based approach to parameter estimation in state-space models having quantized output data

49th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2010.5717022 ◽

2010 ◽

Cited By ~ 3

Author(s):

Damian E. Marelli ◽

Boris I. Godoy ◽

Graham C. Goodwin

Keyword(s):

Parameter Estimation ◽

State Space ◽

State Space Models ◽

Output Data

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On the Bias of the SIR Filter in Parameter Estimation of the Dynamics Process of State Space Models

Distributed Computing and Artificial Intelligence, 12th International Conference - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-19638-1_10 ◽

2015 ◽

pp. 87-95

Author(s):

Tiancheng Li ◽

Sara Rodríguez ◽

Javier Bajo ◽

Juan M. Corchado ◽

Shudong Sun

Keyword(s):

Parameter Estimation ◽

State Space ◽

State Space Models ◽

Dynamics Process

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Online expectation-maximization type algorithms for parameter estimation in general state space models

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). ◽

10.1109/icassp.2003.1201620 ◽

2004 ◽

Cited By ~ 18

Author(s):

C. Andrieu ◽

A. Doucet

Keyword(s):

Parameter Estimation ◽

State Space ◽

Expectation Maximization ◽

State Space Models ◽

General State ◽

General State Space

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Optimal input design for parameter estimation in nonlinear state-space models using Pontryagin's minimum principle

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.12.314 ◽

2015 ◽

Vol 48 (28) ◽

pp. 1319-1324 ◽

Cited By ~ 2

Author(s):

Karel J. Keesman

Keyword(s):

Parameter Estimation ◽

State Space ◽

Minimum Principle ◽

State Space Models ◽

Optimal Input ◽

Input Design ◽

Pontryagin's Minimum Principle ◽

Optimal Input Design ◽

Nonlinear State Space Models ◽

Nonlinear State

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Particle Approximations of the Score and Observed Information Matrix for Parameter Estimation in State–Space Models With Linear Computational Cost

Journal of Computational and Graphical Statistics ◽

10.1080/10618600.2015.1093492 ◽

2016 ◽

Vol 25 (4) ◽

pp. 1138-1157 ◽

Cited By ~ 6

Author(s):

Christopher Nemeth ◽

Paul Fearnhead ◽

Lyudmila Mihaylova

Keyword(s):

Parameter Estimation ◽

State Space ◽

Information Matrix ◽

Computational Cost ◽

State Space Models ◽

Observed Information ◽

Observed Information Matrix

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