Auswahl der wissenschaftlichen Literatur zum Thema „Estimation de l'horizon mobile“
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Zeitschriftenartikel zum Thema "Estimation de l'horizon mobile"
THIVOLLE-CAZAT (Alain) und PIGNARD (Gérôme). „Estimation du volume de bois résineux disponible en France à l'horizon 2010“. Revue Forestière Française, Nr. 3-4 (2001): 317. http://dx.doi.org/10.4267/2042/5243.
Der volle Inhalt der QuelleKumar, Shailesh, und Anant R. Koppar. „Software Estimation Framework for Mobile Application Projects“. International Journal of Productivity Management and Assessment Technologies 7, Nr. 2 (Juli 2019): 26–40. http://dx.doi.org/10.4018/ijpmat.2019070102.
Der volle Inhalt der QuelleKim, Cheong-Hwan, Dae-Seung Ban und Yong-Hwan Lee. „Channel estimation in mobile WiMAX systems“. International Conference on Electrical Engineering 6, Nr. 6 (01.05.2008): 1–13. http://dx.doi.org/10.21608/iceeng.2008.34233.
Der volle Inhalt der QuelleRzeszucinski, Pawel, Daniel Lewandowski und Cajetan T. Pinto. „Mobile device-based shaft speed estimation“. Measurement 96 (Januar 2017): 52–57. http://dx.doi.org/10.1016/j.measurement.2016.10.005.
Der volle Inhalt der QuelleMcGuire, M., K. N. Plataniotis und A. N. Venetsanopoulos. „Robust estimation of mobile terminal position“. Electronics Letters 36, Nr. 16 (2000): 1426. http://dx.doi.org/10.1049/el:20000960.
Der volle Inhalt der QuelleKaur, Anureet, und Kulwant Kaur. „Effort Estimation in Traditional and Agile Mobile Application Development & Testing“. Indonesian Journal of Electrical Engineering and Computer Science 12, Nr. 3 (01.12.2018): 1265. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1265-1272.
Der volle Inhalt der QuelleFernandes, Thiago Soares, Álvaro Freitas Moreira und Érika Cota. „EPE-Mobile-A framework for early performance estimation of mobile applications“. Software: Practice and Experience 48, Nr. 1 (24.08.2017): 85–104. http://dx.doi.org/10.1002/spe.2518.
Der volle Inhalt der QuelleZajic, Alenka G. „Estimation of Mobile Velocities and Direction of Movement in Mobile-to-Mobile Wireless Fading Channels“. IEEE Transactions on Vehicular Technology 61, Nr. 1 (Januar 2012): 130–39. http://dx.doi.org/10.1109/tvt.2011.2175410.
Der volle Inhalt der QuelleKIM, SUNGBOK, und SANGHYUP LEE. „ROBUST MOBILE ROBOT VELOCITY ESTIMATION USING A POLYGONAL ARRAY OF OPTICAL MICE“. International Journal of Information Acquisition 05, Nr. 04 (Dezember 2008): 321–30. http://dx.doi.org/10.1142/s0219878908001715.
Der volle Inhalt der QuelleRöhrig, Christof, und Frank Künemund. „WLAN based Pose Estimation for Mobile Robots“. IFAC Proceedings Volumes 41, Nr. 2 (2008): 10433–38. http://dx.doi.org/10.3182/20080706-5-kr-1001.01768.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleThis 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.
Der volle Inhalt der QuelleThe 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.
Der volle Inhalt der QuelleAlli, Idd Pazi. „Channel estimation in mobile wireless systems“. Thesis, KTH, Signalbehandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98754.
Der volle Inhalt der QuelleAngladon, Vincent. „Room layout estimation on mobile devices“. Phd thesis, Toulouse, INPT, 2018. http://oatao.univ-toulouse.fr/20745/1/ANGLADON_Vincent.pdf.
Der volle Inhalt der QuelleKleynhans, Waldo. „On channel estimation for mobile WiMAX“. Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-01262009-102433/.
Der volle Inhalt der QuelleKasebzadeh, 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.
Der volle Inhalt der QuelleNing, Yu. „Mobile speed estimation for hierarchical wireless network“. Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4298.
Der volle Inhalt der QuelleThe 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.
Der volle Inhalt der QuelleThiagarajan, Arvind. „Probabilistic models for mobile phone trajectory estimation“. Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68497.
Der volle Inhalt der QuelleCataloged 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.
Bücher zum Thema "Estimation de l'horizon mobile"
Casey, Donal. Channel estimation techniques for mobile communications. Dublin: University College Dublin, 1995.
Den vollen Inhalt der Quelle finden1936-, Aggarwal J. K., und United States. National Aeronautics and Space Administration., Hrsg. Positional estimation techniques for an autonomous mobile robot: Final report. Austin, Tex: Computer and Vision Research Center, University of Texas at Austin, 1990.
Den vollen Inhalt der Quelle findenIagnemma, Karl. Mobile robots in rough terrain: Estimation, motion planning, and control with application to planetary rovers. Berlin: Springer, 2010.
Den vollen Inhalt der Quelle findenGötz, 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.
Der volle Inhalt der QuelleHaney, Timothy N. Generation of Global System for Mobile (GSM) signals and their Time Difference of Arrival (TDOA) estimation. Monterey, Calif: Naval Postgraduate School, 2000.
Den vollen Inhalt der Quelle findenWilmot, Chester. Analysis of Louisiana vehicular input data for MOBILE 6. Baton Rouge, La: Louisiana Transportation Research Center, 2008.
Den vollen Inhalt der Quelle findenLuigi, Fortuna, Frasca Mattia, Rizzo Alessandro, Schenato Luca, Zampieri Sandro und SpringerLink (Online service), Hrsg. Modelling, Estimation and Control of Networked Complex Systems. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2009.
Den vollen Inhalt der Quelle findenSteinbrugge, 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.
Den vollen Inhalt der Quelle findenM, Milanese, Hrsg. Bounding approaches to system identification. New York: Plenum Press, 1996.
Den vollen Inhalt der Quelle findenVestli, 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.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Estimation de l'horizon mobile"
Kern, Nicky, und Bernt Schiele. „Towards Personalized Mobile Interruptibility Estimation“. In Location- and Context-Awareness, 134–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11752967_10.
Der volle Inhalt der QuelleDanufane, Fadil, Placido Mursia und Jiang Liu. „Channel Estimation in RIS-Aided Networks“. In Enabling 6G Mobile Networks, 203–20. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74648-3_6.
Der volle Inhalt der QuellePomerleau, Dean A. „Output Appearance Reliability Estimation“. In 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.
Der volle Inhalt der QuellePomerleau, Dean A. „Input Reconstruction Reliability Estimation“. In 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.
Der volle Inhalt der QuelleTalari, Murali Krishna, P. Sai Gautham, N. V. Ramana und S. Kamakshaiah. „Energy Loss Estimation: A Mathematical Approach“. In 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.
Der volle Inhalt der QuelleTamas, Levente, Gheorghe Lazea, Andras Majdik, Mircea Popa und Istvan Szoke. „Position Estimation Techniques for Mobile Robots“. In Robot Motion and Control 2009, 319–28. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-985-5_29.
Der volle Inhalt der QuelleLee, Jongchan, Seung-Jae Yoo und Dong Chun Lee. „Fuzzy Logic Adaptive Mobile Location Estimation“. In 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.
Der volle Inhalt der QuelleCasado, Fernando E., Adrián Nieto, Roberto Iglesias, Carlos V. Regueiro und Senén Barro. „Robust Heading Estimation in Mobile Phones“. In 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.
Der volle Inhalt der QuellePrasad Reddy, P. V. G. D., und CH V. M. K. Hari. „Fuzzy Based PSO for Software Effort Estimation“. In 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.
Der volle Inhalt der QuelleEngels, Florian. „Target Shape Estimation Using an Automotive Radar“. In 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Estimation de l'horizon mobile"
Kim, Minkyong, und Brian Noble. „Mobile network estimation“. In the 7th annual international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/381677.381705.
Der volle Inhalt der QuelleLeakkaw, Puttipong, und Sooksan Panichpapiboon. „Speed estimation through mobile sensing“. In TENCON 2014 - 2014 IEEE Region 10 Conference. IEEE, 2014. http://dx.doi.org/10.1109/tencon.2014.7022319.
Der volle Inhalt der QuelleLeakkaw, Puttipong, und Sooksan Panichpapiboon. „Clearance Estimation through Mobile Sensing“. In 2017 21st International Computer Science and Engineering Conference (ICSEC). IEEE, 2017. http://dx.doi.org/10.1109/icsec.2017.8443796.
Der volle Inhalt der QuelleXiaoyun, Teng, Yuan Jia und Yu Hongyi. „Probability density estimation based on SVM“. In 2009 Global Mobile Congress. IEEE, 2009. http://dx.doi.org/10.1109/gmc.2009.5295893.
Der volle Inhalt der QuelleZajic, Alenka G. „Estimation of Velocities in Mobile-to-Mobile Wireless Fading Channels“. In 2011 IEEE Vehicular Technology Conference (VTC Fall). IEEE, 2011. http://dx.doi.org/10.1109/vetecf.2011.6092883.
Der volle Inhalt der QuellePu, Liang, Jian Liu, Yuan Fang, Wei Li und Zhisen Wang. „Channel Estimation in Mobile Wireless Communication“. In 2010 International Conference on Communications and Mobile Computing (CMC). IEEE, 2010. http://dx.doi.org/10.1109/cmc.2010.201.
Der volle Inhalt der QuelleHutter, A. A., R. Hasholzner und J. S. Hammerschmidt. „Channel estimation for mobile OFDM systems“. In 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.
Der volle Inhalt der QuelleSrinivasan, Sumana, und Krithi Ramamritham. „Contour estimation using collaborating mobile sensors“. In the 2006 workshop. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1160972.1160986.
Der volle Inhalt der Quellede Souza, Laudson Silva, und Gibeon Soares de Aquino. „MEstiAM: Estimation model for mobile applications“. In 2014 9th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2014. http://dx.doi.org/10.1109/cisti.2014.6876949.
Der volle Inhalt der QuelleCai, Zixin, Owen Noel Newton Fernando und Jia Ying Ong. „PoseBuddy : Pose Estimation Workout Mobile Application“. In 2022 International Conference on Cyberworlds (CW). IEEE, 2022. http://dx.doi.org/10.1109/cw55638.2022.00034.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Estimation de l'horizon mobile"
Moore, Terrence, Fikadu Dagefu, Michael Weisman, Robert Drost und Hakan Arslan. Range Estimation of an Ultraviolet Communication Source using a Mobile Sensor. Aberdeen Proving Ground, MD: DEVCOM Army Research Laboratory, September 2022. http://dx.doi.org/10.21236/ad1179957.
Der volle Inhalt der QuelleHabib, Ayman, Yun-Jou Lin, Radhika Ravi, Tamer Shamseldin und Magdy Elbahnasawy. LiDAR-Based Mobile Mapping System for Lane Width Estimation in Work Zone. Purdue University, Januar 2019. http://dx.doi.org/10.5703/1288284316730.
Der volle Inhalt der QuelleClark, G. Radiation Field Simulation and Estimation Algorithms for a Mobile Sensor and a Stationary Unknown Source. Office of Scientific and Technical Information (OSTI), Juli 2012. http://dx.doi.org/10.2172/1048918.
Der volle Inhalt der QuelleApeti, Ablam Estel, und Eyah Denise Edoh. Finding the Missing Stone: Mobile Money and the Quality of Tax Policy and Administration. Institute of Development Studies, Januar 2024. http://dx.doi.org/10.19088/ictd.2024.006.
Der volle Inhalt der QuelleQamer, 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), März 2023. http://dx.doi.org/10.53055/icimod.1017.
Der volle Inhalt der QuelleCai, H., und 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), September 2014. http://dx.doi.org/10.2172/1155133.
Der volle Inhalt der QuelleLee, W. S., Victor Alchanatis und Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, Januar 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
Der volle Inhalt der QuelleDwelling 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.
Der volle Inhalt der Quelle