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Books on the topic 'State and parameter estimations'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Heijden, F. van der, R. P. W. Duin, D. de Ridder, and D. M. J. Tax. Classification, Parameter Estimation and State Estimation. John Wiley & Sons, Ltd, 2004. http://dx.doi.org/10.1002/0470090154.

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2

de Ridder, Dick, David M. J. Tax, Bangjun Lei, et al. Classification, Parameter Estimation and State Estimation. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119152484.

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3

Chernousʹko, F. L. State estimation for dynamic systems. CRC Press, 1994.

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4

Murphy, Katherine A. Estimation of time- and state-dependent delays and other parameters in functional differential equations. ICASE, 1988.

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5

der, Heijden Ferdinand van, ed. Classification, parameter estimation, and state estimation: An engineering approach using MATLAB. Wiley, 2004.

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6

Cecilia, Andreu. Advances in Nonlinear Observer Design for State and Parameter Estimation in Energy Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-38924-5.

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7

Jaulin, Luc. Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics. Springer London, 2001.

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8

Luc, Jaulin, ed. Applied interval analysis: With examples in parameter and state estimation, robust control and robotics. Springer, 2001.

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9

Du, Tan. Joint state-and-parameter estimation of induction-motor drives with application to adaptive field-oriented control. University of Birmingham, 1994.

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10

M, Rasmuson Dale, Mosleh A, U.S. Nuclear Regulatory Commission. Office for Analysis and Evaluation of Operational Data. Division of Safety Programs., Idaho National Engineering and Environmental Laboratory., Lockheed Idaho Technologies Company, and U.S. Nuclear Regulatory Commission., eds. Common-cause failure parameter estimations. Safety Programs Division, Office for Analysis and Evaluation of Operational Data, U.S. Nuclear Regulatory Commission, 1998.

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11

M, Rasmuson Dale, Mosleh A, U.S. Nuclear Regulatory Commission. Office for Analysis and Evaluation of Operational Data. Division of Safety Programs., Idaho National Engineering and Environmental Laboratory., Lockheed Idaho Technologies Company, and U.S. Nuclear Regulatory Commission., eds. Common-cause failure parameter estimations. Safety Programs Division, Office for Analysis and Evaluation of Operational Data, U.S. Nuclear Regulatory Commission, 1998.

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12

M, Rasmuson Dale, Mosleh A, U.S. Nuclear Regulatory Commission. Office for Analysis and Evaluation of Operational Data. Division of Safety Programs., Idaho National Engineering and Environmental Laboratory., and Lockheed Idaho Technologies Company, eds. Common-cause failure parameter estimations. Safety Programs Division, Office for Analysis and Evaluation of Operational Data, U.S. Nuclear Regulatory Commission, 1998.

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13

D, Andrisani, and Dryden Flight Research Facility, eds. Estimating short-period dynamics using an extended Kalman filter. National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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14

D, Andrisani, and Dryden Flight Research Facility, eds. Estimating short-period dynamics using an extended Kalman filter. National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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15

D, Andrisani, and Dryden Flight Research Facility, eds. Estimating short-period dynamics using an extended Kalman filter. National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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16

Kunchenko, I︠U︡ P. Polynomial parameter estimations of close to Gaussian random variables. Shaker, 2003.

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17

Wiesen, Christopher. Learn to Use Maximum Likelihood Parameter Estimation in Stata With the Cardiac Catheterization Diagnostic Dataset (2018). SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526498939.

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18

van Keulen, Bert. H∞-Control for Distributed Parameter Systems: A State-Space Approach. Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4612-0347-6.

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19

Keulen, Bert van. H [infinity]-control for distributed parameter systems: A state space approach. Birkhäuser, 1993.

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20

Baek, Y. Comparison of the time vector method and the state-space method (Eigenvector analysis) for aircraft parameter identification. Cranfield University, College of Aeronautics, 1996.

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21

Chen, Kai. Set membership estimation of state and parameters and operational control of integrated quantity and quality models of water supply and distribution systems. University of Birmingham, 1997.

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22

Kecman, V. State-space models of lumped and distributed systems. Springer-Verlag, 1988.

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23

Baturina, Evgeniya. Shadow cash flow monitoring in assessing the state of economic security. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2132121.

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The monograph reveals a theoretical and methodological approach to monitoring the shadow economy through its new parameter, which is qualitatively different from existing research methods and allows a different look at the problems of unity of methodology and terminology, reliability and comparability of its assessments as a threat to Russia's economic security. The results of the research can be used in the development of the national project "Data Economics" and the implementation of control over the entrepreneurial activities of organizations by the authorities of the Russian Federation. It

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24

Pavlov, Sergey. Methods of catastrophe theory in the phenomenology of phase transitions. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1004276.

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The monograph is devoted to describing the methods of catastrophe theory and building on the basis of these methods, phenomenological models of phase transitions in solids. Methods of constructing structurally stable normal forms of functions, including functions that are imposed on the symmetry conditions. The classification of phenomenological models of phase transitions for two interacting one-component order parameter, two-component and three-component order parameters the number of control parameters varied in the experiment. Theoretical dependence of the anomalies of the physical propert

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25

Tax, David M., and Robert Duin. Classification, Parameter Estimation and State Estimation. Wiley & Sons, Incorporated, John, 2005.

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26

Sawo, Felix. Nonlinear State and Parameter Estimation of Spatially Distributed Systems. KIT Scientific Publishing, 2009.

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27

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, Bangjun Lei, and Ming Feng. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Limited, John, 2017.

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28

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, Bangjun Lei, and Guangzhu Xu. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Incorporated, John, 2017.

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29

Heijden, Ferdinand van der, Robert Duin, Dick de Ridder, and David M. J. Tax. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley, 2004.

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30

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, Bangjun Lei, and Guangzhu Xu. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Incorporated, John, 2017.

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31

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, and Robert P. Duin. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Incorporated, John, 2007.

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32

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, and Robert P. Duin. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Incorporated, John, 2005.

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33

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, and Robert P. W. Duin. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons Australia, Limited, John, 2005.

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34

Heijden, Ferdinand van der, Dick de Ridder, David M. J. Tax, Robert P. Duin, and Bangjun Lei. Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB. Wiley & Sons, Limited, John, 2017.

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35

Modified Multiple Model Adaptive Estimation (M3AE) for Simultaneous Parameter and State Estimation. Storming Media, 1998.

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36

Borodovsky, Mark, and Josif A. Boguslavskiy. Dynamic Systems Models: New Methods of Parameter and State Estimation. Springer, 2016.

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37

Borodovsky, Mark, and Josif A. Boguslavskiy. Dynamic Systems Models: New Methods of Parameter and State Estimation. Springer, 2014.

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38

Borodovsky, Mark, and Josif A. Boguslavskiy. Dynamic Systems Models: New Methods of Parameter and State Estimation. Springer, 2018.

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39

Lee, Kiseok. Adaptive estimation of random parameter regression models by state space representation methods. 1990.

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40

Vossepoel, Femke C. Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem. Springer International Publishing AG, 2023.

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41

Leeuwen, Peter Jan van, Femke Vossepoel, and Geir Evensen. Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem. Springer International Publishing AG, 2022.

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42

Cecilia, Andreu. Advances in Nonlinear Observer Design for State and Parameter Estimation in Energy Systems. Springer, 2023.

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43

Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics. Springer, 2011.

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44

Theoretical and experimental investigations of sensor location for optimal aeroelastic system state estimation. NASA Dryden Flight Research Center, 1985.

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45

Common-Cause Failure Parameter Estimations. United States Government Printing Office, 1998.

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46

Isermann, Rolf. Automatic Control: World Congress, 1987 : Linear Systems Theory, Stochastic Control and State Estimation, Distributed Parameter Systems (Ifac Procee). Elsevier Science Publishing Company, 1988.

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47

Philippe R.L. De Vallière. State and parameter estimation in batch reactors for the purpose of inferring on-line the rate of heat production. 1989.

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48

Harlim, John. Data-Driven Computational Methods: Parameter and Operator Estimations. Cambridge University Press, 2018.

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49

Harlim, John. Data-Driven Computational Methods: Parameter and Operator Estimations. Cambridge University Press, 2018.

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50

Generalized Residual Multiple Model Adaptive Estimation of Parameters and States. Storming Media, 2003.

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