Search Results - PARAMETER ESTIMATION

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  1. 1

    Optomechanical parameter estimation by Shan Zheng Ang, Glen I Harris, Warwick P Bowen, Mankei Tsang

    Published in New Journal of Physics (2013-01-01)
    “…We propose a statistical framework for the problem of parameter estimation from a noisy optomechanical system. …”
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  2. 2

    Sample Size and Test Length for Item Parameter Estimate and Exam Parameter Estimate by Riswan Riswan

    “…This paper aims (1) to determine the sample size (N) on the stability of the item parameter (2) to determine the length (n) test on the stability of the estimate parameter examinee (3) to determine the effect of the model on the stability of the item and the parameter to examine (4) to find out Effect of sample size and test length on item stability and examinee parameter estimates (5) Effect of sample size, test length, and model on item stability and examinee parameter estimates. …”
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  3. 3

    Parameters Estimation of Three-Phase Induction Motor Using the Parameter Estimator App by Fares Bettahar, Sabrina Abdeddaim, Omar Charrouf, Achour Betka, Michael Short, Laid Guerrida, Belahcene taha lemdjed

    Published in ITEGAM-JETIA (2025-09-01)
    “…This study presents a parameter estimation technique using MATLAB’s Parameter Estimator app to determine key parameters, including stator and rotor resistances, leakage and magnetizing inductances, moment of inertia, and friction coefficient. …”
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  4. 4

    Abduction as Incomplete Parameter Estimation by Moto Kamiura

    Subjects: “…Parameter Estimation…”
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  5. 5

    Incompatibility in quantum parameter estimation by Federico Belliardo, Vittorio Giovannetti

    Published in New Journal of Physics (2021-01-01)
    Subjects: “…quantum parameter estimation…”
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  6. 6

    Comparison of estimation limits for quantum two-parameter estimation by Simon K. Yung, Lorcán O. Conlon, Jie Zhao, Ping Koy Lam, Syed M. Assad

    Published in Physical Review Research (2024-09-01)
    “…Measurement estimation bounds for local quantum multiparameter estimation, which provide lower bounds on possible measurement uncertainties, have so far been formulated in two ways: by extending the classical Cramér-Rao bound (e.g., the quantum Cramér-Rao bound and the Nagaoka Cramér-Rao bound) and by incorporating the parameter estimation framework with the uncertainty principle, as in the Lu-Wang uncertainty relation. …”
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  7. 7

    Bootstrap Tests for the Location Parameter under the Skew-Normal Population with Unknown Scale Parameter and Skewness Parameter by Rendao Ye, Bingni Fang, Weixiao Du, Kun Luo, Yiting Lu

    Published in Mathematics (2022-03-01)
    Subjects: “…location parameter…”
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    Article


  8. 8

    Estimation of car braking parameters by Marijus Radavičius, Saulius Nagurnas

    Published in Lietuvos Matematikos Rinkinys (2004-12-01)
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  9. 9

    Estimation of car braking parameters by Marijus Radavičius, Saulius Nagurnas

    Published in Lietuvos Matematikos Rinkinys (2004-12-01)
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  10. 10

    Valid lower bound for all estimators in quantum parameter estimation by Jing Liu, Haidong Yuan

    Published in New Journal of Physics (2016-01-01)
    “…The widely used quantum Cramér–Rao bound (QCRB) sets a lower bound for the mean square error of unbiased estimators in quantum parameter estimation, however, in general QCRB is only tight in the asymptotical limit. …”
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    Article


  11. 11

    The Influence of Parameter Estimation Bounds on Velocity Estimation in PSInSAR by Timo Balz, Mostafa Ewais

    Published in Remote Sensing (2025-02-01)
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  12. 12

    QuanEstimation: An open-source toolkit for quantum parameter estimation by Mao Zhang, Huai-Ming Yu, Haidong Yuan, Xiaoguang Wang, Rafał Demkowicz-Dobrzański, Jing Liu

    Published in Physical Review Research (2022-10-01)
    “…To fill this vacancy, here we present a Python-Julia-based open-source toolkit for quantum parameter estimation, which includes many well-used mathematical bounds and optimization methods. …”
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    Article


  13. 13

    On the estimates of the Laplace integrals on the small parameter by I. Ye. Ovchar, O. B. Skaskiv

    Published in Karpatsʹkì Matematičnì Publìkacìï (2011-06-01)
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  14. 14

    Parameter Estimation for Robotic Manipulator Systems by Qianfeng Zhu, Zhihong Man, Zhenwei Cao, Jinchuan Zheng, Hai Wang

    Published in Machines (2022-05-01)
    Subjects: “…parameter estimation…”
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    Article


  15. 15

    Gradient method with AFEM for parameter-estimation by Roland Becker

    Published in Selecciones Matemáticas (2023-06-01)
    Subjects: “…parameter estimation…”
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  16. 16

    Quantum parameter estimation with general dynamics by Haidong Yuan, Chi-Hang Fred Fung

    Published in npj Quantum Information (2017-04-01)
    “…New tools for quantum parameter estimation: more general and more efficient Measuring the parameters of interest with high precision is essential for science and technology, where the main quest is to find the ultimate precision limit and the optimal schemes to attain it. …”
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  17. 17

    Estimation of the Hurst Parameter in Spot Volatility by Yicun Li, Yuanyang Teng

    Published in Mathematics (2022-05-01)
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  18. 18

    A Note On the Estimation of the Poisson Parameter by S. S. Chitgopekar

    “…It is interesting to note that either method fails to give unique estimates of these parameters unless the error probabilities are functionally related. …”
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  19. 19

    Sequential parameter estimation for stochastic systems by G. A. Kivman

    Published in Nonlinear Processes in Geophysics (2003-01-01)
    “…It is shown that the SIR is capable of estimating the system parameters and to predict the evolution of the system with a remarkably better accuracy than the EnKF. …”
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  20. 20

    Incorporating Parameter Estimability Into Model Selection by Jake M. Ferguson, Mark L. Taper, Mark L. Taper, Rosana Zenil-Ferguson, Marie Jasieniuk, Bruce D. Maxwell

    Published in Frontiers in Ecology and Evolution (2019-11-01)
    “…We investigate a class of information criteria based on the informational complexity criterion (ICC), which penalizes model fit based on the degree of dependency among parameters. In addition to existing forms of ICC, we develop a new complexity measure that uses the coefficient of variation matrix, a measure of parameter estimability, and a novel compound criterion that accounts for both the number of parameters and their informational complexity. …”
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