Optimality of CUSUM Rule Approximations in Change-Point Detection Problems: Application to Nonlinear State–Space Systems

IEEE Transactions on Information Theory ◽

10.1109/tit.2008.929964 ◽

2008 ◽

Vol 54 (11) ◽

pp. 5102-5112 ◽

Author(s):

Ghislain Verdier ◽

Nadine Hilgert ◽

Jean-Pierre Vila

Keyword(s):

State Space ◽

Change Point ◽

Change Point Detection ◽

Space Systems ◽

State Space Systems ◽

Point Detection ◽

Nonlinear State

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On-line change-point detection (for state space models) using multi-process Kalman filters

Linear Algebra and its Applications ◽

10.1016/s0024-3795(98)10132-5 ◽

1998 ◽

Vol 284 (1-3) ◽

pp. 125-135 ◽

Author(s):

Martin Daumer ◽

Markus Falk

Keyword(s):

State Space ◽

Change Point ◽

Kalman Filters ◽

Change Point Detection ◽

State Space Models ◽

On Line ◽

Point Detection

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Multi-innovation gradient identification for input nonlinear state space systems∗∗This work was supported by the National Natural Science Foundation of China (No. 61304138) and the PAPD of Jiangsu Higher Education Institutions.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2015.09.076 ◽

2015 ◽

Vol 48 (8) ◽

pp. 853-858 ◽

Author(s):

Xuehai Wang ◽

Yanjun Liu ◽

Feng Ding

Keyword(s):

Higher Education ◽

State Space ◽

Natural Science ◽

Higher Education Institutions ◽

Space Systems ◽

State Space Systems ◽

Nonlinear State

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Asymptotically Optimal Change Point Detection for Composite Hypothesis in State Space Models

IEEE Transactions on Information Theory ◽

10.1109/tit.2020.3029096 ◽

2021 ◽

Vol 67 (1) ◽

pp. 485-505

Author(s):

Cheng-Der Fuh

Keyword(s):

State Space ◽

Change Point ◽

Change Point Detection ◽

State Space Models ◽

Composite Hypothesis ◽

Asymptotically Optimal ◽

Point Detection ◽

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Modelling and multi-innovation parameter identification for Hammerstein nonlinear state space systems using the filtering technique

Mathematical and Computer Modelling of Dynamical Systems ◽

10.1080/13873954.2016.1142455 ◽

2016 ◽

Vol 22 (2) ◽

pp. 113-140 ◽

Author(s):

Xuehai Wang ◽

Feng Ding

Keyword(s):

Parameter Identification ◽

State Space ◽

Space Systems ◽

State Space Systems ◽

Filtering Technique ◽

Nonlinear State

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Guaranteed Characterization of Capture Basins of Nonlinear State-Space Systems

Informatics in Control, Automation and Robotics - Lecture Notes in Electrical Engineering ◽

10.1007/978-3-540-85640-5_20 ◽

2008 ◽

pp. 265-272 ◽

Author(s):

Nicolas Delanoue ◽

Luc Jaulin ◽

Laurent Hardouin ◽

Mehdi Lhommeau

Keyword(s):

State Space ◽

Space Systems ◽

State Space Systems ◽

Nonlinear State

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'Unobserved' Monte Carlo method for identification of partially observed nonlinear state space systems. Part II. Counting process observations

Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187) ◽

10.1109/cdc.2000.912214 ◽

2002 ◽

Author(s):

V. Solo

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

State Space ◽

Counting Process ◽

Space Systems ◽

Partially Observed ◽

State Space Systems ◽

Nonlinear State

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Sequential Change-Point Detection in State-Space Models

Sequential Analysis ◽

10.1080/07474946.2012.665676 ◽

2012 ◽

Vol 31 (2) ◽

pp. 145-171

Author(s):

Boris Brodsky

Keyword(s):

State Space ◽

Change Point ◽

Change Point Detection ◽

State Space Models ◽

Sequential Change ◽

Point Detection

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Expectation maximization estimation for a class of input nonlinear state space systems by using the Kalman smoother

Signal Processing ◽

10.1016/j.sigpro.2017.12.019 ◽

2018 ◽

Vol 145 ◽

pp. 295-303 ◽

Author(s):

Junxia Ma ◽

Ouyang Wu ◽

Biao Huang ◽

Feng Ding

Keyword(s):

State Space ◽

Expectation Maximization ◽

Space Systems ◽

Kalman Smoother ◽

State Space Systems ◽

Nonlinear State

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Identification of fully parameterized linear and nonlinear state-space systems by projected gradient search

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)34845-0 ◽

2003 ◽

Vol 36 (16) ◽

pp. 711-716 ◽

Author(s):

Vincent Verdult ◽

Niek Bergboer ◽

Michel Verhaegen

Keyword(s):

State Space ◽

Space Systems ◽

Gradient Search ◽

Projected Gradient ◽

State Space Systems ◽

Linear And Nonlinear ◽

Nonlinear State

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Change Point Detection in a State Space Framework Applied to Climate Change in Europe

10.1007/978-3-030-86973-1_45 ◽

2021 ◽

pp. 641-652

Author(s):

Magda Monteiro ◽

Marco Costa

Keyword(s):

Climate Change ◽

State Space ◽

Change Point ◽

Change Point Detection ◽

Point Detection

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