Relevant bibliographies by topics / Constrained state estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Constrained state estimation'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Constrained state estimation"

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Gomez-Quiles, Catalina, Hugo A. Gil, Antonio de la Villa Jaen, and Antonio Gomez-Exposito. "Equality-constrained bilinear state estimation." IEEE Transactions on Power Systems 28, no. 2 (2013): 902–10. http://dx.doi.org/10.1109/tpwrs.2012.2215058.

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Quintana, V. H., B. W. Scott, and A. Y. Chikhani. "Constrained Power System State Estimation." IFAC Proceedings Volumes 20, no. 5 (1987): 7–12. http://dx.doi.org/10.1016/s1474-6670(17)55409-9.

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Hu, Yudong, Changsheng Gao, and Wuxing Jing. "Joint State and Parameter Estimation for Hypersonic Glide Vehicles Based on Moving Horizon Estimation via Carleman Linearization." Aerospace 9, no. 4 (2022): 217. http://dx.doi.org/10.3390/aerospace9040217.

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Aimed at joint state and parameter estimation problems in hypersonic glide vehicle defense, a novel moving horizon estimation algorithm via Carleman linearization is developed in this paper. First, the maneuver characteristic parameters that reflect the target maneuver law are extended into the state vector, and a dynamic tracking model applicable to various hypersonic glide vehicles is constructed. To improve the estimation accuracy, constraints such as path and parameter change amplitude constraints in flight are taken into account, and the estimation problem is transformed into a nonlinear
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Nie, S., J. Zhu, and Y. Luo. "Simultaneous estimation of land surface scheme states and parameters using the ensemble Kalman filter: identical twin experiments." Hydrology and Earth System Sciences 15, no. 8 (2011): 2437–57. http://dx.doi.org/10.5194/hess-15-2437-2011.

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Abstract. The performance of the ensemble Kalman filter (EnKF) in soil moisture assimilation applications is investigated in the context of simultaneous state-parameter estimation in the presence of uncertainties from model parameters, soil moisture initial condition and atmospheric forcing. A physically based land surface model is used for this purpose. Using a series of identical twin experiments in two kinds of initial parameter distribution (IPD) scenarios, the narrow IPD (NIPD) scenario and the wide IPD (WIPD) scenario, model-generated near surface soil moisture observations are assimilat
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Liu, Yuanyuan, Yaqiong Fu, Huipin Lin, Jingbiao Liu, Mingyu Gao, and Zhiwei He. "A New Constrained State Estimation Method Based on Unscented H∞ Filtering." Applied Sciences 10, no. 23 (2020): 8484. http://dx.doi.org/10.3390/app10238484.

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The unscented Kalman filter (UKF) is widely used in many fields. When the unscented Kalman filter is combined with the H∞ filter (HF), the obtained unscented H∞ filtering (UHF) is very suitable for state estimation of nonlinear non-Gaussian systems. However, the application of state estimation is often limited by physical laws and mathematical models on some occasions. The standard unscented H∞ filtering always performs poorly under this situation. To solve this problem, this paper improves the UHF algorithm based on state constraints and studies the UHF algorithm based on the projection metho
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Mare, José B., and José A. De Doná. "Symmetry between constrained reference tracking and constrained state estimation." Automatica 45, no. 1 (2009): 207–11. http://dx.doi.org/10.1016/j.automatica.2008.06.020.

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Prakash, J., Sachin C. Patwardhan, and Sirish L. Shah. "Constrained State Estimation Using Particle Filters." IFAC Proceedings Volumes 41, no. 2 (2008): 6472–77. http://dx.doi.org/10.3182/20080706-5-kr-1001.01091.

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Dasgupta, Kalyan, and K. S. Swarup. "Tie-line constrained distributed state estimation." International Journal of Electrical Power & Energy Systems 33, no. 3 (2011): 569–76. http://dx.doi.org/10.1016/j.ijepes.2010.12.010.

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Wang, Yanyan, and Yingsong Li. "Sparse Multipath Channel Estimation Using Norm Combination Constrained Set-Membership NLMS Algorithms." Wireless Communications and Mobile Computing 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8140702.

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A norm combination penalized set-membership NLMS algorithm with l0 and l1 independently constrained, which is denoted as l0 and l1 independently constrained set-membership (SM) NLMS (L0L1SM-NLMS) algorithm, is presented for sparse adaptive multipath channel estimations. The L0L1SM-NLMS algorithm with fast convergence and small estimation error is implemented by independently exerting penalties on the channel coefficients via controlling the large group and small group channel coefficients which are implemented by l0 and l1 norm constraints, respectively. Additionally, a further improved L0L1SM
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Korres, George N., and Theodore A. Alexopoulos. "A Constrained Ordering for Solving the Equality Constrained State Estimation." IEEE Transactions on Power Systems 27, no. 4 (2012): 1998–2005. http://dx.doi.org/10.1109/tpwrs.2012.2194745.

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Dissertations / Theses on the topic "Constrained state estimation"

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Yan, Jun. "Constrained model predictive control, state estimation and coordination." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3206875.

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Thesis (Ph. D.)--University of California, San Diego, 2006.<br>Title from first page of PDF file (viewed May 3, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 106-110).
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Lopez, Negrete de la Fuente Rodrigo. "Nonlinear Programming Sensitivity Based Methods for Constrained State Estimation." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/174.

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Model based control schemes, such as nonlinear model predictive control, assume that the full state vector of the plant is known for feedback control. However, in reality this is not always true. Most times only a set of noisy measurements are available, and thus, the unmeasured states need to be inferred from these measurements. This is done in combination with a detailed model of the system. The most common nonlinear state estimation methods do not have a means to deal with bounds or constraints on the states in an efficient or systematical way. These bounds and constraints are important in
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Venturino, Antonello. "Constrained distributed state estimation for surveillance missions using multi-sensor multi-robot systems." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST118.

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Les algorithmes distribués sont dorénavant présents dans de nombreux aspects de l'Automatique avec des applications pour des systèmes multi-robots, des réseaux de capteurs, couvrant des sujets tels que la commande, l'estimation d'état, la détection de défauts, la détection et l'atténuation des cyberattaques sur les systèmes cyber-physiques, etc. En effet, les systèmes distribués sont confrontés à des problèmes tels que l'extensibilité à un grand nombre d'agents et la communication entre eux. Dans les applications de systèmes multi-agents (par exemple, flotte de robots mobiles, réseaux de capte
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Duan, Zhansheng. "State Estimation with Unconventional and Networked Measurements." ScholarWorks@UNO, 2010. http://scholarworks.uno.edu/td/1133.

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This dissertation consists of two main parts. One is about state estimation with two types of unconventional measurements and the other is about two types of network-induced state estimation problems. The two types of unconventional measurements considered are noise-free measurements and set measurements. State estimation with them has numerous real supports. For state estimation with noisy and noise-free measurements, two sequential forms of the batch linear minimum mean-squared error (LMMSE) estimator are obtained to reduce the computational complexity. Inspired by the estimation with
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Mook, Daniel Joseph. "Measurement covariance-constrained estimation for poorly modeled dynamic systems." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/49776.

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Pajic, Slobodan. "Power System State Estimation and Contingency Constrained Optimal Power Flow - A Numerically Robust Implementation." Digital WPI, 2007. https://digitalcommons.wpi.edu/etd-dissertations/240.

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The research conducted in this dissertation is divided into two main parts. The first part provides further improvements in power system state estimation and the second part implements Contingency Constrained Optimal Power Flow (CCOPF) in a stochastic multiple contingency framework. As a real-time application in modern power systems, the existing Newton-QR state estimation algorithms are too slow and too fragile numerically. This dissertation presents a new and more robust method that is based on trust region techniques. A faster method was found among the class of Krylov subspace iterative
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Merlinge, Nicolas. "State estimation and trajectory planning using box particle kernels." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS425/document.

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L'autonomie d'un engin aérospatial requière de disposer d'une boucle de navigation-guidage-pilotage efficace et sûre. Cette boucle intègre des filtres estimateurs et des lois de commande qui doivent dans certains cas s'accommoder de non-linéarités sévères et être capables d'exploiter des mesures ambiguës. De nombreuses approches ont été développées à cet effet et parmi celles-ci, les approches particulaires présentent l'avantage de pouvoir traiter de façon unifiée des problèmes dans lesquels les incertitudes d’évolution du système et d’observation peuvent être soumises à des lois statistiques
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Steinig, Simeon [Verfasser], and Kunibert G. [Akademischer Betreuer] Siebert. "Adaptive finite elements for state-constrained optimal control problems - convergence analysis and a posteriori error estimation / Simeon Steinig. Betreuer: Kunibert G. Siebert." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2014. http://d-nb.info/106430897X/34.

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Sircoulomb, Vincent. "Étude des concepts de filtrage robuste aux méconnaissances de modèles et aux pertes de mesures. Application aux systèmes de navigation." Thesis, Vandoeuvre-les-Nancy, INPL, 2008. http://www.theses.fr/2008INPL093N/document.

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La résolution d'un problème d'estimation de l'état d'un système nécessite de disposer d'un modèle régissant l'évolution des variables d'état et de mesurer de manière directe ou indirecte l'ensemble ou une partie de ces variables d'état. Les travaux exposés dans ce mémoire de thèse portent sur la problématique d'estimation en présence de méconnaissances de modèle et de pertes de capteurs. La première partie de ce travail constitue la synthèse d'un dispositif d'estimation d'état pour systèmes non linéaires. Cela consiste à sélectionner un estimateur d'état et convenablement le régler, puis à con
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Sircoulomb, Vincent. "Étude des concepts de filtrage robuste aux méconnaissances de modèles et aux pertes de mesures. Application aux systèmes de navigation." Electronic Thesis or Diss., Vandoeuvre-les-Nancy, INPL, 2008. http://www.theses.fr/2008INPL093N.

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La résolution d'un problème d'estimation de l'état d'un système nécessite de disposer d'un modèle régissant l'évolution des variables d'état et de mesurer de manière directe ou indirecte l'ensemble ou une partie de ces variables d'état. Les travaux exposés dans ce mémoire de thèse portent sur la problématique d'estimation en présence de méconnaissances de modèle et de pertes de capteurs. La première partie de ce travail constitue la synthèse d'un dispositif d'estimation d'état pour systèmes non linéaires. Cela consiste à sélectionner un estimateur d'état et convenablement le régler, puis à con
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Books on the topic "Constrained state estimation"

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Ariyur, Kartik. Navigation with Signals and Constraints of Opportunity: Exploiting Unstructured Environments for State Estimation. Elsevier Science & Technology Books, 2019.

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Beenakker, Carlo W. J. Extreme eigenvalues of Wishart matrices: application to entangled bipartite system. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.37.

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This article describes the application of random matrix theory (RMT) to the estimation of the bipartite entanglement of a quantum system, with particular emphasis on the extreme eigenvalues of Wishart matrices. It first provides an overview of some spectral properties of unconstrained Wishart matrices before introducing the problem of the random pure state of an entangled quantum bipartite system consisting of two subsystems whose Hilbert spaces have dimensions M and N respectively with N ≤ M. The focus is on the smallest eigenvalue which serves as an important measure of entanglement between
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Book chapters on the topic "Constrained state estimation"

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Shi, Dawei, Ling Shi, and Tongwen Chen. "A Constrained Optimization Approach." In Event-Based State Estimation. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26606-0_5.

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Kurzhanski, Alexander B., and Alexander N. Daryin. "State Estimation and State Constrained Control." In Dynamic Programming for Impulse Feedback and Fast Controls. Springer London, 2019. http://dx.doi.org/10.1007/978-1-4471-7437-0_9.

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Bergounioux, M., and K. Kunisch. "Augmented Lagrangian Algorithms for State Constrained Optimal Control Problems." In Control and Estimation of Distributed Parameter Systems. Birkhäuser Basel, 1998. http://dx.doi.org/10.1007/978-3-0348-8849-3_3.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "Event-Based State Estimation under Constrained Bit Rate: An Encoding-Decoding Approach." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-9.

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Wang, Yudong, Jingchun Wang, and Bo Liu. "Constrained Nonlinear State Estimation – A Differential Evolution Based Moving Horizon Approach." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74205-0_122.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "Gain-Scheduled State Estimation for Discrete-Time Complex Networks under Bit-Rate Constraints." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-2.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "Conclusions and Future Topics." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-10.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "An Event-Triggered Encoding Approach to Control of Linear Systems under Bit Rate Conditions." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-8.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "Observer-Based Consensus Control for Discrete-Time Multi-Agent Systems with Coding-Decoding Communication Protocol." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-5.

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Wang, Licheng, Zidong Wang, and Guoliang Wei. "Stabilization of Linear Discrete-Time Systems over Resource-Constrained Networks under Dynamical Multiple Description Coding Scheme." In Data-Rate-Constrained State Estimation and Control of Complex Networked Systems. CRC Press, 2024. http://dx.doi.org/10.1201/9781003534853-7.

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Conference papers on the topic "Constrained state estimation"

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Yu, Yifan, Shengjie Xiu, and Daniel P. Palomar. "Robust and Constrained Estimation of State-Space Models: A Majorization-Minimization Approach." In 2024 58th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2024. https://doi.org/10.1109/ieeeconf60004.2024.10942697.

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Hu, Wang, Zeyi Jiang, Hamed Mohsenian-Rad, and Jay A. Farrell. "Convex Reformulation of Information Constrained Linear State Estimation with Mixed-Binary Variables for Outlier Accommodation." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886080.

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Shang, Jun, Hanwen Zhang, Jing Zhou, and Tongwen Chen. "Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886537.

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Cheung, Catherine, Bruno Rocha, Julio Valdés, and Jobin Puthuparampil. "Improved Load Estimation And Fatigue Life Tracking Demonstrated On Multiple Platforms Using The Signal Approximation Method." In Vertical Flight Society 72nd Annual Forum & Technology Display. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11475.

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This paper presents the results from several load estimation methods developed at the National Research Council Canada (NRC) which enable the estimation of helicopter loads and tracking load exceedances and fatigue damage for a targeted component using computational intelligence techniques. The approach relies only on flight state and control system (FSCS) parameters, such as those recorded by a flight data recorder (FDR), and can also be applied to legacy aircraft or to those aircraft not equipped with HUMS. The methodologies adapt to the input data available so are not constrained to one par
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Gomez-Quiles, Catalina, Hugo A. Gil, Antonio de la Villa Jaen, and Antonio Gomez-Exposito. "Equality-constrained bilinear state estimation." In 2013 IEEE Power & Energy Society General Meeting. IEEE, 2013. http://dx.doi.org/10.1109/pesmg.2013.6672832.

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Goel, Ankit, and Dennis S. Bernstein. "Adaptive State Estimation with Subspace-Constrained State Correction." In 2020 American Control Conference (ACC). IEEE, 2020. http://dx.doi.org/10.23919/acc45564.2020.9147916.

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Ebinger, Bradley, Nidhal Bouaynaya, Robi Polikar, and Roman Shterenberg. "Constrained state estimation in particle filters." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178732.

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Kuklišová Pavelková, Lenka. "Bayesian State Estimation Using Constrained Zonotopes." In 20th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0012230900003543.

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Teixeira, B. O. S., J. Chandrasekar, L. A. B. Torres, L. A. Aguirre, and D. S. Bernstein. "State estimation for equality-constrained linear systems." In 2007 46th IEEE Conference on Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/cdc.2007.4434800.

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Surana, Amit, Matthew O. Williams, Manfred Morari, and Andrzej Banaszuk. "Koopman operator framework for constrained state estimation." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263649.

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Reports on the topic "Constrained state estimation"

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Zeller, Lucas, Daniel McGrath, Louis Sass, Shad O’Neel, Christopher McNeil, and Emily Baker. Beyond glacier-wide mass balances : parsing seasonal elevation change into spatially resolved patterns of accumulation and ablation at Wolverine Glacier, Alaska. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48497.

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We present spatially distributed seasonal and annual surface mass balances of Wolverine Glacier, Alaska, from 2016 to 2020. Our approach accounts for the effects of ice emergence and firn compaction on surface elevation changes to resolve the spatial patterns in mass balance at 10 m scale. We present and compare three methods for estimating emergence velocities. Firn compaction was constrained by optimizing a firn model to fit three firn cores. Distributed mass balances showed good agreement with mass-balance stakes (RMSE = 0.67 m w.e., r = 0.99, n = 41) and ground-penetrating radar surveys (R
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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