Littérature scientifique sur le sujet « Estimation de l'horizon mobile »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Sommaire
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Estimation de l'horizon mobile ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "Estimation de l'horizon mobile"
THIVOLLE-CAZAT (Alain) et PIGNARD (Gérôme). « Estimation du volume de bois résineux disponible en France à l'horizon 2010 ». Revue Forestière Française, no 3-4 (2001) : 317. http://dx.doi.org/10.4267/2042/5243.
Texte intégralKumar, Shailesh, et Anant R. Koppar. « Software Estimation Framework for Mobile Application Projects ». International Journal of Productivity Management and Assessment Technologies 7, no 2 (juillet 2019) : 26–40. http://dx.doi.org/10.4018/ijpmat.2019070102.
Texte intégralKim, Cheong-Hwan, Dae-Seung Ban et Yong-Hwan Lee. « Channel estimation in mobile WiMAX systems ». International Conference on Electrical Engineering 6, no 6 (1 mai 2008) : 1–13. http://dx.doi.org/10.21608/iceeng.2008.34233.
Texte intégralRzeszucinski, Pawel, Daniel Lewandowski et Cajetan T. Pinto. « Mobile device-based shaft speed estimation ». Measurement 96 (janvier 2017) : 52–57. http://dx.doi.org/10.1016/j.measurement.2016.10.005.
Texte intégralMcGuire, M., K. N. Plataniotis et A. N. Venetsanopoulos. « Robust estimation of mobile terminal position ». Electronics Letters 36, no 16 (2000) : 1426. http://dx.doi.org/10.1049/el:20000960.
Texte intégralKaur, Anureet, et Kulwant Kaur. « Effort Estimation in Traditional and Agile Mobile Application Development & ; Testing ». Indonesian Journal of Electrical Engineering and Computer Science 12, no 3 (1 décembre 2018) : 1265. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1265-1272.
Texte intégralFernandes, Thiago Soares, Álvaro Freitas Moreira et Érika Cota. « EPE-Mobile-A framework for early performance estimation of mobile applications ». Software : Practice and Experience 48, no 1 (24 août 2017) : 85–104. http://dx.doi.org/10.1002/spe.2518.
Texte intégralZajic, Alenka G. « Estimation of Mobile Velocities and Direction of Movement in Mobile-to-Mobile Wireless Fading Channels ». IEEE Transactions on Vehicular Technology 61, no 1 (janvier 2012) : 130–39. http://dx.doi.org/10.1109/tvt.2011.2175410.
Texte intégralKIM, SUNGBOK, et SANGHYUP LEE. « ROBUST MOBILE ROBOT VELOCITY ESTIMATION USING A POLYGONAL ARRAY OF OPTICAL MICE ». International Journal of Information Acquisition 05, no 04 (décembre 2008) : 321–30. http://dx.doi.org/10.1142/s0219878908001715.
Texte intégralRöhrig, Christof, et Frank Künemund. « WLAN based Pose Estimation for Mobile Robots ». IFAC Proceedings Volumes 41, no 2 (2008) : 10433–38. http://dx.doi.org/10.3182/20080706-5-kr-1001.01768.
Texte intégralThèses sur le sujet "Estimation de l'horizon mobile"
Ranjbar, Gigasari Roza. « Model Predictive Controller for large-scale systems - Application to water networks ». Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Lille Douai, 2024. http://www.theses.fr/2024MTLD0002.
Texte intégralThis thesis addresses the challenge of optimizing the management of canals, a complex task due to their extensive scale and distinctive attributes, including intricate dynamics, considerable time delays, and minimal bottom slopes. Specifically, the central goal is to ensure the navigability of the network, which involves maintaining safe water levels for vessel travel, through control theory. More precisely, the water levels must remain within a predefined range around a setpoint. Additionally, typical aims encompass reducing operational costs and enhancing the equipment’s life expectancy. In this regard, another objective in the management of such networks is replacing the possible sensors across canals by applying a moving robot to take the required measurements. To accomplish effective management, it becomes imperative to ensure efficient control over hydraulic structures such as gates, pumps, and locks. To this end, a control algorithm is introduced based on an existing model derived from the Saint-Venant equations. The modeling approach simplified the original complex description providing adaptability and facilitating the systematic integration of both current and delayed information. However, the resulting model formulation falls within the category of delayed descriptor systems, necessitating extensions to standard control and state estimation tools. Model predictive control and moving horizon estimation methods can be readily tailored for this formulation, while also adapting physical and operational constraints seamlessly. Given the extensive nature of canals, an evaluation of the digital twin was untaken to address the critical need for advanced tools in the management of such networks. By harnessing the capabilities of digital twins, we aimed to enhance our understanding of canal dynamics, past scenarios, and management strategies. This evaluation sought to bridge the gap between theory and practical implementation, offering a tangible means to playback past events, test diverse management approaches, and ultimately equip decision-makers with robust criteria for informed and effective network management.The methodologies presented above are applied to a practical case study, a canal in the northern region of France. The objective is to validate the efficacy of these approaches in a real-world context.While centralized MPC provides resilience through its receding-horizon approach, its deterministic nature limits its ability to systematically address uncertainties. To effectively tackle these system uncertainties, the implementation of Stochastic MPC (SMPC) has been adopted. SMPC integrates probabilistic descriptions into control design, offering a methodical approach to accommodating uncertainties. In this context, the application of SMPC is interconnected with a mobile robot aimed at replacing existing sensors along the canal to capture measurements. Consequently, a part of this thesis focuses on the design of SMPC in conjunction with a mobile robot. This approach has been applied to an ASCE Test canal to evaluate its effectiveness
Poquin, Didier. « Estimation de la verticale subjective en tangage : contribution de l'horizon visuel apparent ». Grenoble 2, 1998. http://www.theses.fr/1998GRE29016.
Texte intégralThe factors determining spatial orientation in the median plane have been relatively neglected, although this dimension is the preferential plane of human displacements and the alert reaction in case of danger. Concerning pitch orientation, the observers point of view is an essential factor to estimate the surface slant. In this frame, the hypothesis according to pitch visually perceived vertical (pitch VPV) is assessed from visually perceived eye level (VPEL) has been assumed. It has been asked to an observer, seated in a dark room, to assess the subjective vertical by adjusting to the gravity direction a luminous and rectangular surface (the rod), and in other hand to judge the eye level by setting a luminous target in the horizontal plane getting through his eyes. The first part of results shows that the pitch VPV assessments have its own mechanisms whose the main factors are the geometrical cues relative to the form of the rod and the subjective eye level. Those factors could explain the lack of correlation observed between roll and pitch rod adjustments to the gravity direction and the systematic deviation of the pitch VPV, 'top of the rod toward the observer'. The second part of results describes two processes involving the VPEL to estimate the pitch VPV. The first processes, called 'mechanism of cenfered orthogonalisation', leads to adjust the rod perpendicular to an imaginary line getting through the center of the surface to the subjective eye level. This process occurs when VPEL errors are small. The second mechanism, called 'mechanism of surcompensation', is observed when the subject believes that the rod is put up or down relative to his perceived eye level. The consequence is a erroned compensation from this subjective point of view. This mechanism occurs when VPEL errors are large. The last experimental section confirms, with a visual scene, the existence of mechanisms of centered orthogonalisation or surcompensation to adjust a rod to the gravity direction in the median plane. In conclusion, the subjective eye level is considered as the point of view from which an observer calculates the slant orientation of planar surfaces. In other words, the determination of the pitch orientation of an object initially needs the estimation of the observer's localization in the environment
Patel, Chirag S. « Channel modeling and estimation for mobile-to-mobile OFDM communications ». Thesis, Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13552.
Texte intégralAlli, Idd Pazi. « Channel estimation in mobile wireless systems ». Thesis, KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98754.
Texte intégralAngladon, Vincent. « Room layout estimation on mobile devices ». Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/20745/1/ANGLADON_Vincent.pdf.
Texte intégralKleynhans, Waldo. « On channel estimation for mobile WiMAX ». Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-01262009-102433/.
Texte intégralKasebzadeh, Parinaz. « Parameter Estimation for Mobile Positioning Applications ». Licentiate thesis, Linköpings universitet, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-141877.
Texte intégralNing, Yu. « Mobile speed estimation for hierarchical wireless network ». Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4298.
Texte intégralThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 14, 2006) Includes bibliographical references.
Zhou, Bin. « Mobile velocity estimation in multipath fading channels ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0005/MQ42710.pdf.
Texte intégralThiagarajan, Arvind. « Probabilistic models for mobile phone trajectory estimation ». Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68497.
Texte intégralCataloged from PDF version of thesis.
Includes bibliographical references (p. 157-161).
This dissertation is concerned with the problem of determining the track or trajectory of a mobile device - for example, a sequence of road segments on an outdoor map, or a sequence of rooms visited inside a building - in an energy-efficient and accurate manner. GPS, the dominant positioning technology today, has two major limitations. First, it consumes significant power on mobile phones, making it impractical for continuous monitoring. Second, it does not work indoors. This dissertation develops two ways to address these limitations: (a) subsampling GPS to save energy, and (b) using alternatives to GPS such as WiFi localization, cellular localization, and inertial sensing (with the accelerometer and gyroscope) that consume less energy and work indoors. The key challenge is to match a sequence of infrequent (from sub-sampling) and inaccurate (from WiFi, cellular or inertial sensing) position samples to an accurate output trajectory. This dissertation presents three systems, all using probabilistic models, to accomplish this matching. The first, VTrack, uses Hidden Markov Models to match noisy or sparsely sampled geographic (lat, lon) coordinates to a sequence of road segments on a map. We evaluate VTrack on 800 drive hours of GPS and WiFi localization data collected from 25 taxicabs in Boston. We find that VTrack tolerates significant noise and outages in location estimates, and saves energy, while providing accurate enough trajectories for applications like travel-time aware route planning. CTrack improves on VTrack with a Markov Model that uses "soft" information in the form of raw WiFi or cellular signal strengths, rather than geographic coordinates. It also uses movement and turn "hints" from the accelerometer and compass to improve accuracy. We implement CTrack on Android phones, and evaluate it on cellular signal data from over 126 (1,074 miles) hours of driving data. CTrack can retrieve over 75% of a user's drive accurately on average, even from highly inaccurate (175 metres raw position error) GSM data. iTrack uses a particle filter to combine inertial sensing data from the accelerometer and gyroscope with WiFi signals and accurately track a mobile phone indoors. iTrack has been implemented on the iPhone, and can track a user to within less than a metre when walking with the phone in the hand or pants pocket, over 5 x more accurately than existing WiFi localization approaches. iTrack also requires very little manual effort for training, unlike existing localization systems that require a user to visit hundreds or thousands of locations in a building and mark them on a map.
by Arvind Thiagarajan.
Ph.D.
Livres sur le sujet "Estimation de l'horizon mobile"
Casey, Donal. Channel estimation techniques for mobile communications. Dublin : University College Dublin, 1995.
Trouver le texte intégral1936-, Aggarwal J. K., et United States. National Aeronautics and Space Administration., dir. Positional estimation techniques for an autonomous mobile robot : Final report. Austin, Tex : Computer and Vision Research Center, University of Texas at Austin, 1990.
Trouver le texte intégralIagnemma, Karl. Mobile robots in rough terrain : Estimation, motion planning, and control with application to planetary rovers. Berlin : Springer, 2010.
Trouver le texte intégralGötz, Alexander. Coherent Time Difference of Arrival Estimation Techniques for Frequency Hopping GSM Mobile Radio Signals. München : Oldenbourg Wissenschaftsverlag Verlag, 2013. http://dx.doi.org/10.1524/9783486748628.
Texte intégralHaney, Timothy N. Generation of Global System for Mobile (GSM) signals and their Time Difference of Arrival (TDOA) estimation. Monterey, Calif : Naval Postgraduate School, 2000.
Trouver le texte intégralWilmot, Chester. Analysis of Louisiana vehicular input data for MOBILE 6. Baton Rouge, La : Louisiana Transportation Research Center, 2008.
Trouver le texte intégralLuigi, Fortuna, Frasca Mattia, Rizzo Alessandro, Schenato Luca, Zampieri Sandro et SpringerLink (Online service), dir. Modelling, Estimation and Control of Networked Complex Systems. Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2009.
Trouver le texte intégralSteinbrugge, Karl V. Dwelling and mobile home monetary losses due to the 1989 Loma Prieta, California, earthquake with an emphasis on loss estimation. Washington : U.S. G.P.O., 1994.
Trouver le texte intégralM, Milanese, dir. Bounding approaches to system identification. New York : Plenum Press, 1996.
Trouver le texte intégralVestli, Sjur Jonas. Fast, accurate and robust estimation of mobile robot position and orientation : A dissertation submitted to the Swiss Federal Institute of Technology, Zurich, for the degree of Doctor of Technical Sciences. Zurich : Swiss Federal Institute of Technology, 1995.
Trouver le texte intégralChapitres de livres sur le sujet "Estimation de l'horizon mobile"
Kern, Nicky, et Bernt Schiele. « Towards Personalized Mobile Interruptibility Estimation ». Dans Location- and Context-Awareness, 134–50. Berlin, Heidelberg : Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11752967_10.
Texte intégralDanufane, Fadil, Placido Mursia et Jiang Liu. « Channel Estimation in RIS-Aided Networks ». Dans Enabling 6G Mobile Networks, 203–20. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74648-3_6.
Texte intégralPomerleau, Dean A. « Output Appearance Reliability Estimation ». Dans Neural Network Perception for Mobile Robot Guidance, 117–31. Boston, MA : Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3192-0_8.
Texte intégralPomerleau, Dean A. « Input Reconstruction Reliability Estimation ». Dans Neural Network Perception for Mobile Robot Guidance, 133–50. Boston, MA : Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3192-0_9.
Texte intégralTalari, Murali Krishna, P. Sai Gautham, N. V. Ramana et S. Kamakshaiah. « Energy Loss Estimation : A Mathematical Approach ». Dans Mobile Communication and Power Engineering, 292–97. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35864-7_42.
Texte intégralTamas, Levente, Gheorghe Lazea, Andras Majdik, Mircea Popa et Istvan Szoke. « Position Estimation Techniques for Mobile Robots ». Dans Robot Motion and Control 2009, 319–28. London : Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-985-5_29.
Texte intégralLee, Jongchan, Seung-Jae Yoo et Dong Chun Lee. « Fuzzy Logic Adaptive Mobile Location Estimation ». Dans Lecture Notes in Computer Science, 626–34. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30141-7_92.
Texte intégralCasado, Fernando E., Adrián Nieto, Roberto Iglesias, Carlos V. Regueiro et Senén Barro. « Robust Heading Estimation in Mobile Phones ». Dans From Bioinspired Systems and Biomedical Applications to Machine Learning, 180–90. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19651-6_18.
Texte intégralPrasad Reddy, P. V. G. D., et CH V. M. K. Hari. « Fuzzy Based PSO for Software Effort Estimation ». Dans Information Technology and Mobile Communication, 227–32. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20573-6_36.
Texte intégralEngels, Florian. « Target Shape Estimation Using an Automotive Radar ». Dans Smart Mobile In-Vehicle Systems, 271–90. New York, NY : Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9120-0_16.
Texte intégralActes de conférences sur le sujet "Estimation de l'horizon mobile"
Kim, Minkyong, et Brian Noble. « Mobile network estimation ». Dans the 7th annual international conference. New York, New York, USA : ACM Press, 2001. http://dx.doi.org/10.1145/381677.381705.
Texte intégralLeakkaw, Puttipong, et Sooksan Panichpapiboon. « Speed estimation through mobile sensing ». Dans TENCON 2014 - 2014 IEEE Region 10 Conference. IEEE, 2014. http://dx.doi.org/10.1109/tencon.2014.7022319.
Texte intégralLeakkaw, Puttipong, et Sooksan Panichpapiboon. « Clearance Estimation through Mobile Sensing ». Dans 2017 21st International Computer Science and Engineering Conference (ICSEC). IEEE, 2017. http://dx.doi.org/10.1109/icsec.2017.8443796.
Texte intégralXiaoyun, Teng, Yuan Jia et Yu Hongyi. « Probability density estimation based on SVM ». Dans 2009 Global Mobile Congress. IEEE, 2009. http://dx.doi.org/10.1109/gmc.2009.5295893.
Texte intégralZajic, Alenka G. « Estimation of Velocities in Mobile-to-Mobile Wireless Fading Channels ». Dans 2011 IEEE Vehicular Technology Conference (VTC Fall). IEEE, 2011. http://dx.doi.org/10.1109/vetecf.2011.6092883.
Texte intégralPu, Liang, Jian Liu, Yuan Fang, Wei Li et Zhisen Wang. « Channel Estimation in Mobile Wireless Communication ». Dans 2010 International Conference on Communications and Mobile Computing (CMC). IEEE, 2010. http://dx.doi.org/10.1109/cmc.2010.201.
Texte intégralHutter, A. A., R. Hasholzner et J. S. Hammerschmidt. « Channel estimation for mobile OFDM systems ». Dans Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324). IEEE, 1999. http://dx.doi.org/10.1109/vetecf.1999.797145.
Texte intégralSrinivasan, Sumana, et Krithi Ramamritham. « Contour estimation using collaborating mobile sensors ». Dans the 2006 workshop. New York, New York, USA : ACM Press, 2006. http://dx.doi.org/10.1145/1160972.1160986.
Texte intégralde Souza, Laudson Silva, et Gibeon Soares de Aquino. « MEstiAM : Estimation model for mobile applications ». Dans 2014 9th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2014. http://dx.doi.org/10.1109/cisti.2014.6876949.
Texte intégralCai, Zixin, Owen Noel Newton Fernando et Jia Ying Ong. « PoseBuddy : Pose Estimation Workout Mobile Application ». Dans 2022 International Conference on Cyberworlds (CW). IEEE, 2022. http://dx.doi.org/10.1109/cw55638.2022.00034.
Texte intégralRapports d'organisations sur le sujet "Estimation de l'horizon mobile"
Moore, Terrence, Fikadu Dagefu, Michael Weisman, Robert Drost et Hakan Arslan. Range Estimation of an Ultraviolet Communication Source using a Mobile Sensor. Aberdeen Proving Ground, MD : DEVCOM Army Research Laboratory, septembre 2022. http://dx.doi.org/10.21236/ad1179957.
Texte intégralHabib, Ayman, Yun-Jou Lin, Radhika Ravi, Tamer Shamseldin et Magdy Elbahnasawy. LiDAR-Based Mobile Mapping System for Lane Width Estimation in Work Zone. Purdue University, janvier 2019. http://dx.doi.org/10.5703/1288284316730.
Texte intégralClark, G. Radiation Field Simulation and Estimation Algorithms for a Mobile Sensor and a Stationary Unknown Source. Office of Scientific and Technical Information (OSTI), juillet 2012. http://dx.doi.org/10.2172/1048918.
Texte intégralApeti, Ablam Estel, et Eyah Denise Edoh. Finding the Missing Stone : Mobile Money and the Quality of Tax Policy and Administration. Institute of Development Studies, janvier 2024. http://dx.doi.org/10.19088/ictd.2024.006.
Texte intégralQamer, Faisal M., Sravan Shrestha, Kiran Shakya, Birendra Bajracharya, Shib Nandan Shah, Ram Krishna Regmi, Salik Paudel et al. Operational in-season rice area estimation through Earth observation data in Nepal - working paper. International Centre for Integrated Mountain Development (ICIMOD), mars 2023. http://dx.doi.org/10.53055/icimod.1017.
Texte intégralCai, H., et M. Wang. Estimation of Emission Factors and Particulate Black Carbon and Organic Carbon from Stationary, Mobile, and Non-point Sources in the United States for Incorporation into GREET. Office of Scientific and Technical Information (OSTI), septembre 2014. http://dx.doi.org/10.2172/1155133.
Texte intégralLee, W. S., Victor Alchanatis et Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, janvier 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
Texte intégralDwelling and mobile home monetary losses due to the 1989 Loma Prieta, California, earthquake with an emphasis on loss estimation. US Geological Survey, 1994. http://dx.doi.org/10.3133/b1939b.
Texte intégral