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Littérature scientifique sur le sujet « Estimation »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 25 juillet 2025

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Articles de revues sur le sujet "Estimation"

Bai, Wenyuan, Xinhui Zhang, Zhen Gao, Shuyu Xie, Ke Peng, and Yu Chen. "Sensorless Coestimation of Temperature and State-of-Charge for Lithium-Ion Batteries Based on a Coupled Electrothermal Model." International Journal of Energy Research 2023 (February 6, 2023): 1–18. http://dx.doi.org/10.1155/2023/4021256.

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Accurate estimations of the temperature and the state-of-charge (SOC) are of extreme importance for the safety of lithium-ion battery operation. Traditional battery temperature and SOC estimation methods often omit the relation between battery temperature and SOC, which may lead to significant errors in the estimations. This study presents a coupled electrothermal battery model and a coestimation method for simultaneously estimating the temperature and SOC of lithium-ion batteries. The coestimation method is performed by a coupled model-based dual extended Kalman filter (DEKF). The coupled est

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IRFAGUTAMI, NI PUTU NIA, I. GUSTI AYU MADE SRINADI, and I. WAYAN SUMARJAYA. "PERBANDINGAN REGRESI ROBUST PENDUGA MM DENGAN METODE RANDOM SAMPLE CONSENSUS DALAM MENANGANI PENCILAN." E-Jurnal Matematika 3, no. 2 (2014): 45. http://dx.doi.org/10.24843/mtk.2014.v03.i02.p065.

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The presence of outliers in observation can result in biased in parameter estimation using ordinary least square (OLS). Robust regression MM-estimator is one of the estimations methods that able to obtain a robust estimator against outliers. Random sample consensus (ransac) is another method that can be used to construct a model for observations data and also estimating a robust estimator against outliers. Based on the study, ransac obtained model with less biased estimator than robust regression MM-estimator.

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Thanoon, Shaymaa Riyadh. "A comparison between Bayes estimation and the estimation of the minimal unbiased quadratic Standard of the bi-division variance analysis model in the presence of interaction." Tikrit Journal of Pure Science 25, no. 2 (2020): 116. http://dx.doi.org/10.25130/j.v25i2.966.

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In this study, the variance compounds parameters of the mixed bi-division variance analysis sample are estimated. This estimation is obtained, by Bayes quadratic unbiased estimator. The second way to estimate variance compounds parameters of a suggested tow-way analysis of variance mixed model with interaction. estimation is done out by the approach called (MINQUÉ). The estimation approach is conducted on true obtained from departments at the college of agriculture/university of Mosul. These data represent the development of growing various kinds of tomato so that the development represents th

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Liu, Bing, Zhen Chen, Xiangdong Liu, and Fan Yang. "An Efficient Nonlinear Filter for Spacecraft Attitude Estimation." International Journal of Aerospace Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/540235.

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Increasing the computational efficiency of attitude estimation is a critical problem related to modern spacecraft, especially for those with limited computing resources. In this paper, a computationally efficient nonlinear attitude estimation strategy based on the vector observations is proposed. The Rodrigues parameter is chosen as the local error attitude parameter, to maintain the normalization constraint for the quaternion in the global estimator. The proposed attitude estimator is performed in four stages. First, the local attitude estimation error system is described by a polytopic linea

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Wu, Renzhi, Bolin Ding, Xu Chu, et al. "Learning to be a statistician." Proceedings of the VLDB Endowment 15, no. 2 (2021): 272–84. http://dx.doi.org/10.14778/3489496.3489508.

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Estimating the number of distinct values (NDV) in a column is useful for many tasks in database systems, such as columnstore compression and data profiling. In this work, we focus on how to derive accurate NDV estimations from random (online/offline) samples. Such efficient estimation is critical for tasks where it is prohibitive to scan the data even once. Existing sample-based estimators typically rely on heuristics or assumptions and do not have robust performance across different datasets as the assumptions on data can easily break. On the other hand, deriving an estimator from a principle

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Talakua, Mozart W., and Jefri Tipka. "ESTIMASI PARAMETER DISTRIBUSI EKPONENSIAL PADA LOKASI TERBATAS." BAREKENG: Jurnal Ilmu Matematika dan Terapan 1, no. 2 (2007): 1–7. http://dx.doi.org/10.30598/barekengvol1iss2pp1-7.

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The common method in Estimating Parameter Distribution Exponential at Finite Location is Maximum Likelihood Estimation (MLE).The best estimator is consistent estimator. Because of The Mean Square Error (MSE) can be used in comparing some detectable estimators that it had looking for with Maximum Likelihood Estimation (MLE) so can find the consistent estimator in Estimating Parameter Distribution Exponential At Finite Location

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Sugiyama, Masashi, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, and Ichiro Takeuchi. "Density-Difference Estimation." Neural Computation 25, no. 10 (2013): 2734–75. http://dx.doi.org/10.1162/neco_a_00492.

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We address the problem of estimating the difference between two probability densities. A naive approach is a two-step procedure of first estimating two densities separately and then computing their difference. However, this procedure does not necessarily work well because the first step is performed without regard to the second step, and thus a small estimation error incurred in the first stage can cause a big error in the second stage. In this letter, we propose a single-shot procedure for directly estimating the density difference without separately estimating two densities. We derive a nonp

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Chamidah, Nur, Budi Lestari, I. Nyoman Budiantara, and Dursun Aydin. "Estimation of Multiresponse Multipredictor Nonparametric Regression Model Using Mixed Estimator." Symmetry 16, no. 4 (2024): 386. http://dx.doi.org/10.3390/sym16040386.

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In data analysis using a nonparametric regression approach, we are often faced with the problem of analyzing a set of data that has mixed patterns, namely, some of the data have a certain pattern and the rest of the data have a different pattern. To handle this kind of datum, we propose the use of a mixed estimator. In this study, we theoretically discuss a developed estimation method for a nonparametric regression model with two or more response variables and predictor variables, and there is a correlation between the response variables using a mixed estimator. The model is called the multire

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Zerdali, Emrah, and Murat Barut. "Extended Kalman Filter Based Speed-Sensorless Load Torque and Inertia Estimations with Observability Analysis for Induction Motors." Power Electronics and Drives 3, no. 1 (2018): 115–27. http://dx.doi.org/10.2478/pead-2018-0002.

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Abstract This paper aims to introduce a novel extended Kalman filter (EKF) based estimator including observability analysis to the literature associated with the high performance speed-sensorless control of induction motors (IMs). The proposed estimator simultaneously performs the estimations of stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, load torque including the viscous friction term, and reciprocal of total inertia by using measured stator phase currents and voltages. The inertia estimation is done since it varies with the load coupled to t

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Baran Kaya, Tuğba, and Sedef Çelik Demirci. "Examination of the Estimation Skills and Strategies of Pre-Service Elementary Mathematics Teachers." International Journal of Research in Education and Science 8, no. 2 (2022): 243–61. http://dx.doi.org/10.46328/ijres.2897.

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The present study aimed to determine the estimation skills of elementary education pre-service mathematics teachers and the strategies they adopt in estimation. The case study methodology was employed in the study, and the participants included 37 volunteering students attending the fourth grade in the Primary Education Mathematics Instruction Department at a university located in the Central Anatolia Region in Turkey. The study data were collected with an 8-item Estimation Strategy Test developed by the authors. The test included numerosity, computational, and measurement estimation questions

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Thèses sur le sujet "Estimation"

Yu, Kan Chi Kent. "Harmonic State Estimation and Transient State Estimation." Thesis, University of Canterbury. Electrical and Computer Engineering, 2006. http://hdl.handle.net/10092/1108.

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This thesis describes the algorithms and techniques developed for harmonic state estimation and transient state estimation, which can be used to identify the location of disturbance sources in an electrical power system. The previous harmonic state estimation algorithm is extended to include the estimation of time-varying harmonics using an adaptive Kalman filter. The proposed method utilises two covariance noise models to overcome the divergence problem in traditional Kalman filters. Moreover, it does not require an optimal covariance noise matrix of the Kalman filter to be used. The co

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Telmoudi, Fedya. "Estimation and misspecification Risks in VaR estimation." Thesis, Lille 3, 2014. http://www.theses.fr/2014LIL30061/document.

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Dans cette thèse, nous étudions l'estimation de la valeur à risque conditionnelle (VaR) en tenant compte du risque d'estimation et du risque de modèle. Tout d'abord, nous considérons une méthode en deux étapes pour estimer la VaR. La première étape évalue le paramètre de volatilité en utilisant un estimateur quasi maximum de vraisemblance généralisé (gQMLE) fondé sur une densité instrumentale h. La seconde étape estime un quantile des innovations à partir du quantile empirique des résidus obtenus dans la première étape. Nous donnons des conditions sous lesquelles l'estimateur en deux étapes de

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Hoff, J. C. "Aircraft parameter estimation by estimation - before - modelling technique." Thesis, Cranfield University, 1995. http://dspace.lib.cranfield.ac.uk/handle/1826/10748.

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The use of the estímation-before-modellíng (EBM) two step identification procedure for the determination of aircraft aerodynamic derivatives from flight test data is analysed and illustrated. In the first step of the identification procedure the usual Extended Kalman Filter (EKF) associated with the Modified Bryson-Frazíer (MBF) smoother is compared with a new alterative filtering and smoothing process. The new smoother is simpler and less computationally demanding than the MBF smoother. However, its main advantage is that it enables simultaneous data smoothing with state derivative estimation

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Reynard, D. M. "Nonlinear estimation." Thesis, University of Newcastle Upon Tyne, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336142.

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Mu, Yingfei. "Boundary Estimation." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/25195.

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The existing statistical methods do not provide a satisfactory solution to determining the spatial pattern in spatially referenced data, which is often required by research in many areas including geology, agriculture, forestry, marine science and epidemiology for identifying the source of the unusual environmental factors associated with a certain phenomenon. This work provides a novel algorithm which can be used to delineate the boundary of an area of hot spots accurately and e ciently. Our algorithm, rst of all, does not assume any pre-speci ed geometric shapes for the change-curve. Second

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Völcker, Björn. "Performance Analysis of Parametric Spectral Estimators." Doctoral thesis, KTH, Signals, Sensors and Systems, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3323.

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Baba, Harra M'hammed. "Estimation de densités spectrales d'ordre élevé." Rouen, 1996. http://www.theses.fr/1996ROUES023.

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Dans cette thèse nous construisons des estimateurs de la densité spectrale du cumulant, pour un processus strictement homogène et centré, l'espace des temps étant l'espace multidimensionnel, euclidien réel ou l'espace multidimensionnel des nombres p-adiques. Dans cette construction nous avons utilisé la méthode de lissage de la trajectoire et un déplacement dans le temps ou la méthode de fenêtres spectrales. Sous certaines conditions de régularité, les estimateurs proposés sont asymptotiquement sans biais et convergents. Les procédures d'estimation exposées peuvent trouver des applications dan

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Verma, Vishash. "Improved Slope Estimation in Organic Field-Effect Transistor Mobility Estimation." Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1618703169092189.

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Chauvin, Jonathan. "Estimation et contrôle d’un moteur HCCI. Estimation des systèmes périodiques." Paris, ENMP, 2006. http://www.theses.fr/2006ENMP1387.

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La combustion homogène Diesel (HCCI : Homogeneous Charge Compression Ignition) est caractérisée par un très fort taux de recirculation de gaz brûlés (EGR : Exhaust Gas Recirculation). Cette technique de combustion permet d’augmenter la qualité de mélange et la dilution dans le cylindre, tout en réduisant la formation des polluants. Malheureusement, ce procédé nuit à la stabilité de la combustion. Un compromis est nécessaire entre la stabilité de combustion et les performances du moteur, quantifiées en terme de couple produit, de bruit et d’émissions polluantes. C’est là le rôle du moteur. À fi

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Srinivasarengan, Krishnan. "Estimation d'état, estimation paramétrique et identifiabilité des modèles quasi-LPV." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0059/document.

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Dans cette thèse, deux problèmes liés aux approches basées sur des modèles pour le diagnostic de défauts et l'estimation du niveau de dégradation des équipements dans un bâtiment sont étudiés: la conception d'observateurs adaptatifs pour l'estimation de l'état et des paramètres, et l'analyse de l'identifiabilité des paramètres. La classe des modèles considérés est celle des modèles quasi-linéaires à paramètres variants dans le temps (quasi-LPV) avec paramétrisation affine des matrices d'état. Utilisant l'approche polytopique de Takagi-Sugeno (T-S), deux types d'observateurs sont proposés, un p

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Livres sur le sujet "Estimation"

Dowdy, Penny. Estimation. Crabtree Pub., 2008.

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1949-, Gervais Paul, ed. Estimation. Beauchemin, 1997.

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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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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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Ghosh, Malay, Nitis Mukhopadhyay, and Pranab K. Sen. Sequential Estimation. John Wiley & Sons, Inc., 1997. http://dx.doi.org/10.1002/9781118165928.

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Fourdrinier, Dominique, William E. Strawderman, and Martin T. Wells. Shrinkage Estimation. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02185-6.

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Mislick, Gregory K., and Daniel A. Nussbaum. Cost Estimation. John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781118802342.

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Ross, Gavin J. S. Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8.

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Ross, Gavin J. S. Nonlinear estimation. Springer-Verlag, 1990.

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Ghosh, Malay. Sequential estimation. Wiley, 1997.

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Chapitres de livres sur le sujet "Estimation"

Seong, Junyeong, Sungjun Park, and Kunsoo Huh. "Robust Lane Keeping Control with Estimation of Cornering Stiffness and Model Uncertainty." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_39.

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AbstractThis paper introduces an adaptive lane-keeping control strategy that adapts to varying cornering stiffness while ensuring robustness against uncertainties. The system consists of three blocks: an Interacting Multiple Model (IMM) cornering stiffness estimator, a cornering stiffness uncertainty estimator, and a Robust Model Predictive Controller (RMPC). Improvements in estimation accuracy are achieved through a novel IMM probability derivation method, and the uncertainty estimator utilizes the IMM probability matrix to obtain reliable uncertainty boundaries. Real-time cornering stiffness

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Boos, Denni D., and L. A. Stefanski. "M-Estimation (Estimating Equations)." In Springer Texts in Statistics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4818-1_7.

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Fadali, M. Sami. "Estimation and Estimator Properties." In Introduction to Random Signals, Estimation Theory, and Kalman Filtering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8063-5_5.

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Gao, Zhan, and M. Hashem Pesaran. "Identification and estimation of categorical random coefficient models." In Advanced Studies in Theoretical and Applied Econometrics. Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-48385-1_5.

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AbstractThis paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A generalized method of moments estimation procedure is proposed, also employed by Peter Schmidt and his coauthors to address heterogeneity in time effects in panel data models. Using Monte Carlo simulations, we find that moments of the random coefficients can be estimated reasonably accurately, but large samples are requi

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Hirukawa, Masayuki, Di Liu, Irina Murtazashvili, and Artem Prokhorov. "DS-HECK: double-lasso estimation of Heckman selection model." In Advanced Studies in Theoretical and Applied Econometrics. Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-48385-1_25.

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AbstractWe extend the Heckman (1979) sample selection model by allowing for a large number of controls that are selected using lasso under a sparsity scenario. The standard lasso estimation is known to under-select causing an omitted variable bias in addition to the sample selection bias. We outline the required adjustments needed to restore consistency of lasso-based estimation and inference for vector-valued parameters of interest in such models. The adjustments include double lasso for both the selection equation and main equation and a correction of the variance matrix. We also connect the

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Ross, Gavin J. S. "Models, Parameters, and Estimation." In Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8_1.

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Ross, Gavin J. S. "Transformations of Parameters." In Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8_2.

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Ross, Gavin J. S. "Inference and Stable Transformations." In Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8_3.

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Ross, Gavin J. S. "The Geometry of Nonlinear Inference." In Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8_4.

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Ross, Gavin J. S. "Computing Methods for Nonlinear Modeling." In Nonlinear Estimation. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3412-8_5.

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Actes de conférences sur le sujet "Estimation"

Mballo, Chams, and J. V. R. Prasad. "A Real Time Scheme for Rotating System Component Load Estimation Using Fixed System Measurements." In Vertical Flight Society 74th Annual Forum & Technology Display. The Vertical Flight Society, 2018. http://dx.doi.org/10.4050/f-0074-2018-12768.

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Accurate and real-time load monitoring of vital components located in the rotor system is important for not only inferring usage and estimating fatigue in those components, but also for developing load alleviation /limiting control schemes. An approach previously developed for online estimation of rotor component loads is evaluated in this paper in which a linear time invariant (LTI) model of helicopter coupled body/rotor dynamics is combined with a Linear Quadratic Estimator (LQE), that is designed to correct LTI model state response using fixed system measurements. The estimation fidelity of

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Li, Yonghua, and R. Dyche Anderson. "Switching Adaptive Observer for Lithium-Ion Battery State of Charge Estimation." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6061.

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A switching adaptive observer is proposed for estimation of state of charge (SOC) for lithium ion batteries used in electrified automotive propulsion systems. The base observer includes (i) a parameter estimation subsystem including a recursive parameter estimator for identifying battery parameters and (ii) an open circuit voltage (OCV) estimation subsystem including a nonlinear adaptive observer for estimating battery OCV. A timer as well as excitation level determination decides when the ampere-hour integration based SOC or estimated OCV based SOC is used as output. Using this approach, tran

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Gallego-Mejia, Joseph, and Fabio Gonzalez. "Robust Estimation in Reproducing Kernel Hilbert Space." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai2019120829.

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Our work shows that estimating the mean in a feature space induced by certain kinds of kernels is the same as doing a robust mean estimation using an M-estimator in the original problem space. In particular, we show that calculating the average on a feature space induced by a Gaussian kernel is equivalent to perform robust mean estimation with the Welsch M-estimator. Besides, a new framework is proposed that was used to build four new robust kernels: Tukey’s, Andrews’, Huber’s and Cauchy’s robust kernels. The new robust kernels, combined with kernel matrix factorization clustering algorithm, w

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Zhang, Pushi, Li Zhao, Guoqing Liu, et al. "Independence-aware Advantage Estimation." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/461.

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Most of existing advantage function estimation methods in reinforcement learning suffer from the problem of high variance, which scales unfavorably with the time horizon. To address this challenge, we propose to identify the independence property between current action and future states in environments, which can be further leveraged to effectively reduce the variance of the advantage estimation. In particular, the recognized independence property can be naturally utilized to construct a novel importance sampling advantage estimator with close-to-zero variance even when the Monte-Carlo return

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Huang, Xiaoyu, and Junmin Wang. "Payload Parameter Real-Time Estimation for Lightweight Vehicles." In ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control. ASMEDC, 2011. http://dx.doi.org/10.1115/dscc2011-6045.

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This paper proposes a payload parameter estimation method for lightweight vehicles (LWVs), whose dynamics and control are substantially affected by their payload variations due to the LWVs’ significantly reduced sizes and weights. Accurate and real-time estimation of payload parameters, including payload mass and its onboard planar location, will be helpful for controller designs and load condition monitoring. The proposed payload parameter estimator (PPE) is divided into two parts: tire nominal normal force estimator (NNFE) based on a recursive least squares (RLS) algorithm using signals meas

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Nguyen, Thang, Holly Warner, Hanieh Mohammadi, Dan Simon, and Hanz Richter. "On the State Estimation of an Agonistic-Antagonistic Muscle System." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5304.

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In this paper, an agonistic-antagonistic muscle system is presented. This dual muscle system is based on the Hill muscle model. The problem of estimating the state variables and activation signals of the dual muscle system is addressed. A proposed estimation scheme which combines a super-twisting observer and an input estimator is given to provide a solution to the problem. A backstepping control method is used to track a reference trajectory. Numerical results are conducted to show that the relative error for state estimation is about 1% and that for the unknown inputs is about 3% when the me

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Zhang, Jianwu, and Defeng Xu. "Hierarchical Estimator of Dual Clutch Torques for a Power-Split Hybrid Electric Vehicle." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-8927.

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Abstract For fast drive mode transitions by shifting clutches equipped in the dedicated compound power-split hybrid transmission, correct estimations of pressure and torque of the clutches are crucial for control strategies. A hierarchical estimator is proposed herein for individual estimation of the clutch torques, consisting of not only the reference layer containing the unknown input observer of vehicle resistance and the reduced-order observer of drive shaft torque, but also the estimation layer combining the unknown input observer with the reduced-order observer. The estimator is implemen

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Achicanoy M., Wilson O., and Carlos F. Rodriguez H. "Integration of GPS and Accelerometer Uncertainties to Improve the Estimation of the Pose of Autonomous Vehicles." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40463.

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Uncertainty fusion techniques based on Kalman filtering are commonly used to provide a better estimation of the state of a system. A comparison between three different methods to combine the sensor information in order to improve the estimation of the pose of an autonomous vehicle is presented. Two sensors and their uncertainty models are used to measure the observables states of a process: a Global Positioning System (GPS) and an accelerometer. Given that GPS has low sampling rate and the uncertainty of the position, calculated by double integration from the accelerometer signal, increases wi

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Liu, Chenchen, Yongzhi Li, Kangqi Ma, Duo Zhang, Peijun Bao, and Yadong Mu. "Learning 3-D Human Pose Estimation from Catadioptric Videos." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/118.

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3-D human pose estimation is a crucial step for understanding human actions. However, reliably capturing precise 3-D position of human joints is non-trivial and tedious. Current models often suffer from the scarcity of high-quality 3-D annotated training data. In this work, we explore a novel way of obtaining gigantic 3-D human pose data without manual annotations. In catedioptric videos (\emph{e.g.}, people dance before a mirror), the camera records both the original and mirrored human poses, which provides cues for estimating 3-D positions of human joints. Following this idea, we crawl a lar

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Devezeaux, Jean-Guy. "L’économie globale, le coût du KWh et la sécurisation des fonds." In Méthodologie : estimation du coût du démantèlement. EDP Sciences, 2015. http://dx.doi.org/10.1051/jtsfen/2015met01.

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Rapports d'organisations sur le sujet "Estimation"

Banks, H. T., and Kathleen L. Bihari. Modeling and Estimating Uncertainty in Parameter Estimation. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada447550.

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Bacharach, Miguel, and William J. Vaughan. Household Water Demand Estimation. Inter-American Development Bank, 1994. http://dx.doi.org/10.18235/0011616.

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This working paper addresses the issues: 1) whether there is a simultaneous equations problem when estimating demand for water with multipart rate schedules and, if there is one, what techniques should be used to correct for it; and 2) whether average or marginal price is the relevant measure in estimating the demand function. In addition, the issue is raised of sample selection bias in a rate schedule, combined with a fixed charge for consumption below the level where a block rate tariff per unit consumed. This study uses results from a sample of 685 families from 34 localities in rural Argen

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Candy, J. V. MULTICHANNEL SPECTRAL ESTIMATION: An Approach to Estimating/Analyzing Vibrational Systems. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1592017.

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Li, Ta-Hsin, Benjamin Kedem, and Sid Yakowitz. Asymptotic Normality of the Contraction Mapping Estimator for Frequency Estimation. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada453892.

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Owen, Arthur B. Nonparametric Conditional Estimation. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1454025.

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Bryan, Michael, Stephen Cecchetti, and Rodney L. Wiggins II. Efficient Inflation Estimation. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/w6183.

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Owen, Arthur B. Nonparametric Conditional Estimation. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada590998.

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Uhlig, Harald, Toru Kitagawa, and Raffaella Giacomini. Estimation Under Ambiguity. The IFS, 2019. http://dx.doi.org/10.1920/wp.cem.2019.2419.

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Tibshirani, R. Local Likelihood Estimation. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1453998.

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Hall, Peter, and R. J. Carroll. Variance Function Estimation in Regression: The Effect of Estimating the Mean. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada198228.

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