Gotowa bibliografia na temat „Recursive Bayesian estimation”
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Artykuły w czasopismach na temat "Recursive Bayesian estimation"
Kárný, Miroslav. "Approximate Bayesian recursive estimation". Information Sciences 285 (listopad 2014): 100–111. http://dx.doi.org/10.1016/j.ins.2014.01.048.
Pełny tekst źródłaKarlsson, R., i F. Gustafsson. "Recursive Bayesian estimation: bearings-only applications". IEE Proceedings - Radar, Sonar and Navigation 152, nr 5 (2005): 305. http://dx.doi.org/10.1049/ip-rsn:20045073.
Pełny tekst źródłaThiemann, M., M. Trosset, H. Gupta i S. Sorooshian. "Bayesian recursive parameter estimation for hydrologic models". Water Resources Research 37, nr 10 (październik 2001): 2521–35. http://dx.doi.org/10.1029/2000wr900405.
Pełny tekst źródłaJemmott, Colin W., i R. Lee Culver. "Recursive Bayesian state estimation for passive sonar localization." Journal of the Acoustical Society of America 127, nr 3 (marzec 2010): 1960. http://dx.doi.org/10.1121/1.3385007.
Pełny tekst źródłaKramer, Stuart C., i Harold W. Sorenson. "Recursive Bayesian estimation using piece-wise constant approximations". Automatica 24, nr 6 (listopad 1988): 789–801. http://dx.doi.org/10.1016/0005-1098(88)90055-6.
Pełny tekst źródłaVasudevan, Sathyanarayanan, Richard H. Anderson, Shawn Kraut, Peter Gerstoft, L. Ted Rogers i Jeffrey L. Krolik. "Recursive Bayesian electromagnetic refractivity estimation from radar sea clutter". Radio Science 42, nr 2 (kwiecień 2007): n/a. http://dx.doi.org/10.1029/2005rs003423.
Pełny tekst źródłaAnyfantaki, Sofia, i Antonis Demos. "Estimation and Properties of a Time-Varying GQARCH(1,1)-M Model". Journal of Probability and Statistics 2011 (2011): 1–39. http://dx.doi.org/10.1155/2011/718647.
Pełny tekst źródłaOdo, Wataru, Daisuke Kimoto, Makoto Kumon i Tomonari Furukawa. "Active Sound Source Localization by Pinnae with Recursive Bayesian Estimation". Journal of Robotics and Mechatronics 29, nr 1 (20.02.2017): 49–58. http://dx.doi.org/10.20965/jrm.2017.p0049.
Pełny tekst źródłaTagade, Piyush, Krishnan S. Hariharan, Priya Gambhire, Subramanya Mayya Kolake, Taewon Song, Dukjin Oh, Taejung Yeo i Seokgwang Doo. "Recursive Bayesian filtering framework for lithium-ion cell state estimation". Journal of Power Sources 306 (luty 2016): 274–88. http://dx.doi.org/10.1016/j.jpowsour.2015.12.012.
Pełny tekst źródłaChen, Yanbo, Feng Liu, Shengwei Mei, Guangyu He, Qiang Lu i Yanlan Fu. "An Improved Recursive Bayesian Approach for Transformer Tap Position Estimation". IEEE Transactions on Power Systems 28, nr 3 (sierpień 2013): 2830–41. http://dx.doi.org/10.1109/tpwrs.2013.2248761.
Pełny tekst źródłaRozprawy doktorskie na temat "Recursive Bayesian estimation"
Hanif, A. "Computational intelligence sequential Monte Carlos for recursive Bayesian estimation". Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1403732/.
Pełny tekst źródłaBaziw, Erick. "Application of Bayesian recursive estimation for seismic signal processing". Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/30715.
Pełny tekst źródłaScience, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
Graduate
Rosén, Olov. "Parallel Stochastic Estimation on Multicore Platforms". Doctoral thesis, Uppsala universitet, Avdelningen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-246859.
Pełny tekst źródłaCoDeR-MP
Misirli, Baysal Feyzan. "Improving efficiency and effectiveness of Bayesian recursive parameter estimation for hydrologic models". Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280488.
Pełny tekst źródłaTowler, Jerry Alwynne. "Autonomous Aerial Localization of Radioactive Point Sources via Recursive Bayesian Estimation and Contour Analysis". Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/43465.
Pełny tekst źródłaPerforming this autonomous analysis comprises five major steps: ingress from a base of operations to the danger zone, initial detection of radioactive material, measurement of the strength of radioactive emissions, analysis of the data to provide position and intensity estimates, and finally egress from the area of interest back to the launch site. In all five steps, time is of critical importance: faster responses promise potentially saved lives.
A time-optimal ingress and egress path planning method solves the first and last steps. Vehicle capabilities and instrument sensitivity inform the development of an efficient search path within the area of interest. Two algorithmsâ a grid-based recursive Bayesian estimator and a novel radiation contour analysis methodâ are presented to estimate the position of radioactive sources using simple gross gamma ray event count data from a nondirectional radiation detector. The latter procedure also correctly estimates the number of sources present and their intensities.
Ultimately, a complete unsupervised mission is developed, requiring minimal initial operator interaction, that provides accurate characterization of the radiation environment of an area of interest as quickly as reasonably possible.
Master of Science
Lavis, Benjamin Mark Mechanical & Manufacturing Engineering Faculty of Engineering UNSW. "Spatially reconfigurable and non-parametric representation of dynamic bayesian beliefs". Publisher:University of New South Wales. Mechanical & Manufacturing Engineering, 2008. http://handle.unsw.edu.au/1959.4/41468.
Pełny tekst źródłaTong, Xianqiao. "Real-time Prediction of Dynamic Systems Based on Computer Modeling". Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/47361.
Pełny tekst źródłaPh. D.
Takami, Kuya. "Non-Field-of-View Acoustic Target Estimation". Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/56892.
Pełny tekst źródłaPh. D.
Steckenrider, John J. "Multi-Bayesian Approach to Stochastic Feature Recognition in the Context of Road Crack Detection and Classification". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/81752.
Pełny tekst źródłaMaster of Science
Humans have an outstanding ability to understand things about the world around them. We learn from our youngest years how to make sense of things and perceive our environment even when it is not easy. To do this, we inherently think in terms of probabilities, updating our belief as we gain new information. The methods introduced here allow an autonomous system to think similarly, by applying a fairly common probabilistic technique to the task of perception and classification. In particular, road cracks are observed and classified using these methods, in order to develop an autonomous road condition monitoring system. The results of this research are promising; cracks are identified and correctly categorized with 92% accuracy, and the additional “intelligence” of the system leads to a 33% improvement in road crack assessment. These methods could be applied in a variety of contexts as the leading edge of robotics research seeks to develop more robust and human-like ways of perceiving the world.
Ndiour, Ibrahima Jacques. "Dynamic curve estimation for visual tracking". Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37283.
Pełny tekst źródłaKsiążki na temat "Recursive Bayesian estimation"
Recursive nonlinear estimation: A geometric approach. Berlin: Springer, 1996.
Znajdź pełny tekst źródłaRecursive Identification and Parameter Estimation. Taylor & Francis Group, 2014.
Znajdź pełny tekst źródłaChen, Hanfu, i Wenxiao Zhao. Recursive Identification and Parameter Estimation. Taylor & Francis Group, 2017.
Znajdź pełny tekst źródłaCzęści książek na temat "Recursive Bayesian estimation"
Catlin, Donald E. "Recursive Linear Estimation (Bayesian Estimation)". W Estimation, Control, and the Discrete Kalman Filter, 125–32. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-4528-5_6.
Pełny tekst źródłaEftekhar Azam, Saeed. "Recursive Bayesian Estimation of Partially Observed Dynamic Systems". W Online Damage Detection in Structural Systems, 7–55. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02559-9_2.
Pełny tekst źródłaPardalos, P., V. Yatsenko i S. Butenko. "Robust Recursive Bayesian Estimation and Quantum Minimax Strategies". W Applied Optimization, 213–32. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/0-306-47536-7_11.
Pełny tekst źródłaMoghadamfalahi, Mohammad, Murat Akcakaya i Deniz Erdogmus. "Active Recursive Bayesian State Estimation for Big Biological Data 1". W Signal Processing and Machine Learning for Biomedical Big Data, 115–32. Boca Raton : Taylor & Francis, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351061223-6.
Pełny tekst źródłaTatsis, Konstantinos E., Vasilis K. Dertimanis i Eleni N. Chatzi. "Adaptive Process and Measurement Noise Identification for Recursive Bayesian Estimation". W Model Validation and Uncertainty Quantification, Volume 3, 361–64. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47638-0_39.
Pełny tekst źródłaKárný, Miroslav, i Ivan Nagy. "Recursive Least Squares Approximation of Bayesian Non-Gaussian/Non-Linear Estimation". W Mutual Impact of Computing Power and Control Theory, 123–34. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2968-2_8.
Pełny tekst źródłaMisirli, Feyzan, Hoshin V. Gupta, Soroosh Sorooshian i Michael Thiemann. "Bayesian recursive estimation of parameter and output uncertainty for watershed models". W Water Science and Application, 113–24. Washington, D. C.: American Geophysical Union, 2003. http://dx.doi.org/10.1029/ws006p0113.
Pełny tekst źródłaAstroza, Rodrigo, Hamed Ebrahimian i Joel P. Conte. "Batch and Recursive Bayesian Estimation Methods for Nonlinear Structural System Identification". W Springer Series in Reliability Engineering, 341–64. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52425-2_15.
Pełny tekst źródłaMomani, Mohammad, i Subhash Chall. "Probabilistic Modelling and Recursive Bayesian Estimation of Trust in Wireless Sensor Networks". W Bayesian Network. Sciyo, 2010. http://dx.doi.org/10.5772/10060.
Pełny tekst źródła"Recursive WeissWeinstein Lower Bounds for DiscreteTime Nonlinear Filtering". W Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking. IEEE, 2009. http://dx.doi.org/10.1109/9780470544198.ch71.
Pełny tekst źródłaStreszczenia konferencji na temat "Recursive Bayesian estimation"
Suvorova, Sofia, Stephen Howard i Bill Moran. "Bayesian recursive estimation on the rotation group". W ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638900.
Pełny tekst źródłaRistic, Branko, i Alfonso Farina. "Recursive Bayesian state estimation from Doppler-shift measurements". W 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). IEEE, 2011. http://dx.doi.org/10.1109/issnip.2011.6146626.
Pełny tekst źródłaAndersonl, Robert Blake, Mitch Pryor i Sheldon Landsberger. "Mobile Robotic Radiation Surveying Using Recursive Bayesian Estimation". W 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). IEEE, 2019. http://dx.doi.org/10.1109/coase.2019.8843064.
Pełny tekst źródłaRust i Jordan. "Recursive Bayesian Estimation Of Effective Defibrillation Shock Intensities". W Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.595759.
Pełny tekst źródłaRust, L. M., i J. B. Jordan. "Recursive Bayesian estimation of effective defibrillation shock intensities". W 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761149.
Pełny tekst źródłaKumon, Makoto, Daisuke Kimoto, Kuya Takami i Tomonari Furukawa. "Acoustic recursive Bayesian estimation for non-field-of-view targets". W 2013 14th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS). IEEE, 2013. http://dx.doi.org/10.1109/wiamis.2013.6616161.
Pełny tekst źródłaMarghi, Yeganeh M., Aziz Kocanaogullari, Murat Akcakaya i Deniz Erdogmus. "A History-based Stopping Criterion in Recursive Bayesian State Estimation". W ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683726.
Pełny tekst źródłaBender, Matt J., Hunter M. McClelland, Andrew Kurdila i Rolf Mueller. "Recursive Bayesian Estimation of Bat Flapping Flight Using Kinematic Trees". W AIAA Modeling and Simulation Technologies Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-0945.
Pełny tekst źródłaXiang, Yijian, Murat Akcakaya, Satyabrata Sen, Deniz Erdogmus i Arye Nehorai. "Target tracking via recursive Bayesian state estimation in radar networks". W 2017 51st Asilomar Conference on Signals, Systems, and Computers. IEEE, 2017. http://dx.doi.org/10.1109/acssc.2017.8335475.
Pełny tekst źródłaWang, Lan, Jinghao Zheng, Fangfang Chen i Jisheng Dai. "Sparse Bayesian Learning for DOA Estimation with Recursive Grid-Refining". W 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2018. http://dx.doi.org/10.1109/sam.2018.8448577.
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