Academic literature on the topic 'The Optimum Detection Probabilities'
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Journal articles on the topic "The Optimum Detection Probabilities"
Al-Ababneh, Nedal, and Hasan Aldiabat. "Optimum consultation for serial distributed detection systems." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2636. http://dx.doi.org/10.11591/ijece.v12i3.pp2636-2644.
Full textFriehe, Tim. "Optimal sanctions and endogeneity of differences in detection probabilities." International Review of Law and Economics 28, no. 2 (June 2008): 150–55. http://dx.doi.org/10.1016/j.irle.2008.02.004.
Full textPateriya, Priyanka, Rakesh Singhai, and Piyush Shukla. "Design and Implementation of Optimum LSD Coded Signal Processing Algorithm in the Multiple-Antenna System for the 5G Wireless Technology." Wireless Communications and Mobile Computing 2022 (February 25, 2022): 1–12. http://dx.doi.org/10.1155/2022/7628814.
Full textSolodov, A. A. "Optimal Poisson Cognitive System with Markov Learning Model." Open Education 25, no. 6 (December 27, 2021): 45–52. http://dx.doi.org/10.21686/1818-4243-2021-6-45-52.
Full textSchmidt, A., C. Kruse, F. Rottensteiner, U. Soergel, and C. Heipke. "NETWORK DETECTION IN RASTER DATA USING MARKED POINT PROCESSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 701–8. http://dx.doi.org/10.5194/isprs-archives-xli-b3-701-2016.
Full textSchmidt, A., C. Kruse, F. Rottensteiner, U. Soergel, and C. Heipke. "NETWORK DETECTION IN RASTER DATA USING MARKED POINT PROCESSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 10, 2016): 701–8. http://dx.doi.org/10.5194/isprsarchives-xli-b3-701-2016.
Full textValdez, Jose W., Kaya Klop-Toker, Michelle P. Stockwell, Loren Fardell, Simon Clulow, John Clulow, and Michael J. Mahony. "Differences in microhabitat selection patterns between a remnant and constructed landscape following management intervention." Wildlife Research 44, no. 3 (2017): 248. http://dx.doi.org/10.1071/wr16172.
Full textYang, Ling, Nathan L. Knight, Yong Li, and Chris Rizos. "Optimal Fault Detection and Exclusion Applied in GNSS Positioning." Journal of Navigation 66, no. 5 (May 17, 2013): 683–700. http://dx.doi.org/10.1017/s0373463313000155.
Full textLubis, Arif Ridho, Santi Prayudani, Muharman Lubis, and Al Khowarizmi. "Decision Making in the Tea Leaves Diseases Detection Using Mamdani Fuzzy Inference Method." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (December 1, 2018): 1273. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1273-1281.
Full textEl Jarroudi, Moussa, Louis Kouadio, Clive H. Bock, Mustapha El Jarroudi, Jürgen Junk, Matias Pasquali, Henri Maraite, and Philippe Delfosse. "A Threshold-Based Weather Model for Predicting Stripe Rust Infection in Winter Wheat." Plant Disease 101, no. 5 (May 2017): 693–703. http://dx.doi.org/10.1094/pdis-12-16-1766-re.
Full textDissertations / Theses on the topic "The Optimum Detection Probabilities"
CHALAN, BYRON PAUL MAZA. "OPTIMUM GROUP DETECTION IN BLOCK TRANSMISSION SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=20529@1.
Full textCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Os sistemas de transmissão em bloco, permitem a transmissão de N símbolos de forma simultânea, seja em modulação de portadora única ou multiportadora. A recepção ótima, no sentido de máxima verossimilhança em canais com multipercursos apresenta um custo computacional elevado de AN, onde A é a ordem da constelação (A igual a 2 para BPSK). Para evitar este alto custo computacional é usual fazer a detecção símbolo a símbolo após a equalização. Nesta dissertação é proposto um receptor com detecção por grupos que apresenta uma complexidade intermediária entre o receptor ótimo e os receptores que utilizam detecção símbolo-a-símbolo em sistemas com transmissão em blocos. O tipo de estrutura idealizada agrupa as componentes do bloco equalizado em grupos e realiza detecção conjunta ótima dos símbolos em cada grupo. Com relação possíveis estratégias de agrupamento foram propostos três métodos, o primeiro método faz uma busca exaustiva pelo agrupamento ótimo e tem como consequência um custo computacional elevado para um número grande de símbolos por bloco. Na procura por algoritmos que evitem uma busca exaustiva pelo agrupamento ótimo, mas que resultem em bons ganhos de desempenho, e a sua aplicação em sistemas com um número elevado de símbolos por bloco, foram propostos dois métodos de agrupamento sub-ótimos e eficientes, cujos receptores apresentaram ganhos de desempenho apreciáveis quando comparados ao receptor convencional.
Block transmission systems allow transmissions of N symbols simultaneously, with single carrier or multi-carrier modulation. Maximum likelihood optimal reception in multipath channels have a high computational cost of AN, where A is the constellation order (A iqual 2 for BPSK). To avoid this cost is usual to make symbol-by-symbol detection after equalization. In this work we propose a receiver with group detection that has a good tradeof between computation complexity and bit error rate performance. The idealized structure groups the components of the equalized block in sub-blocks and does optimal joint detection of the symbols in each sub-block. With relation to possible grouping strategies three methods were proposed. The first one searchs for an optimal grouping and has, as a consequence, a high computational cost for block with a large number of symbols. Sub-optimal efficient algorithms that avoid the exhaustive search for the optimal grouping but show good performance gains and feasible application in systems with large number of symbols per block were proposed. The resulted receivers achieved substantial performance gain in comparison with the conventional symbol-by-symbol receiver.
Williams, Branson D. "Estimating Detection Probabilities in Beach Seine Surveys for Estuarine Fishes." W&M ScholarWorks, 2010. https://scholarworks.wm.edu/etd/1539617892.
Full textBailey, Larissa Lynn. "Estimating detection probabilities for terrestrial salamanders in Great Smoky Mountains National Park." Connect to this title online, 2002. http://www.lib.ncsu.edu/theses/available/etd-08022002-111548/unrestricted/etd.pdf.
Full textChi, Ying. "Calculating posterior probabilities for EM induction landmine detection using MCMC with thermodynamic integration /." Full text available from ProQuest UM Digital Dissertations, 2005. http://0-proquest.umi.com.umiss.lib.olemiss.edu/pqdweb?RQT=305&querySyntax=PQ&searchInterface=1&moreOptState=CLOSED&TS=1184862704&h_pubtitle=&h_pmid=&clientId=22256&JSEnabled=1&SQ=chi%2C+ying&DBId=21651&date=ALL&onDate=&beforeDate=&afterDate=&fromDate=&toDate=&TITLE=&author=&SCH=&subject=&LA=any&MTYPE=all&sortby=REVERSE_CHRON&x=0&y=0.
Full textTerletzky, Patricia A. "Utilizing Remote Sensing and Geospatial Techniques to Determine Detection Probabilities of Large Mammals." DigitalCommons@USU, 2013. https://digitalcommons.usu.edu/etd/1760.
Full textSullivan, Michael R. "Leak detection in gas transmission pipelines." Thesis, Curtin University, 2003. http://hdl.handle.net/20.500.11937/881.
Full textTidström, Lina. "Estimation of Probabilities of Detection for Cracks in Pipes in Swedish Nuclear Power Plants." Thesis, Uppsala University, Department of Mathematics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121427.
Full textOymak, Okan. "Sample size determination for estimation of sensor detection probabilities based on a test variable." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Jun%5FOymak.pdf.
Full textThesis Advisor(s): Lyn R. Whitaker. "June 2007." Includes bibliographical references (p. 95-96). Also available in print.
Uriarte, Toboso Alain. "Optimum Ordering for Coded V-BLAST." Thesis, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23509.
Full textSullivan, Michael R. "Leak detection in gas transmission pipelines." Curtin University of Technology, School of Engineering, 2003. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=15189.
Full textIt was clear early into the investigation that the majority of the errors within the leak detection model were created by random errors from the input field data. These non-systematic errors from the measurement data that included pressure and temperature, produced interference with model output. This interference resembled random “white” noise that was removed by a combination of well established data filtering techniques. The most appropriate process of calculating leak detection flow was determined after analysing the results of different techniques applied to large quantities of actual pipeline operating data. The validation of the on-line techniques developed provides a valuable resource for those wishing to implement similar leak detection schemes elsewhere. Furthermore a software environment was chosen which incorporated an open input and output platform for data that could be interfaced with any operating system. Therefore these techniques can be applied to the numerous Supervisory Control and Data Acquisition (SCADA) systems in operation throughout the gas transmission industry, to provide a low cost solution to leak monitoring.
Books on the topic "The Optimum Detection Probabilities"
Forrest, R. N. A program to compute magnetic anomaly detection probabilities. Monterey, Calif: Naval Postgraduate School, 1988.
Find full textForrest, R. N. A program to compute electric anomaly detection probabilities. Monterey, Calif: Naval Postgraduate School, 1988.
Find full textForrest, R. N. A program to compute magnetic anomaly detection probabilities. 2nd ed. Monterey, Calif: Naval Postgraduate School, 1990.
Find full textTrees, Harry L. Van. Detection, Estimation, and Modulation Theory, Optimum Array Processing, Part IV. New York: John Wiley & Sons, Ltd., 2005.
Find full textDivsalar, Dariush. Multiple symbol differential detection of uncoded and trellis coded MPSK. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1990.
Find full textFesta, Roberto. Optimum inductive methods: A study in inductive probability, Bayesian statistics, and verisimilitude. Dordrecht: Kluwer Academic Publishers, 1993.
Find full textTrees, Harry L. Van. Optimum Array Processing (Detection, Estimation, and Modulation Theory, Part IV). Wiley-Interscience, 2002.
Find full textTrees, Harry L. Van. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory. Wiley & Sons, Limited, John, 2002.
Find full textTrees, Harry L. Van. Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory. Wiley & Sons, Incorporated, John, 2008.
Find full textFesta, R. Optimum Inductive Methods: A Study in Inductive Probability, Bayesian Statistics, and Verisimilitude. Springer, 2010.
Find full textBook chapters on the topic "The Optimum Detection Probabilities"
Festa, Roberto. "The Theory of Inductive Probabilities: Basic Features and Applications." In Optimum Inductive Methods, 13–19. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8131-8_2.
Full textFesta, Roberto. "The Choice of Prior Probabilities: The Subjective, Aprioristic, and Contextual Approaches." In Optimum Inductive Methods, 75–102. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8131-8_7.
Full textHauser, C. E., G. E. Garrard, and J. L. Moore. "Estimating detection rates and probabilities." In Biosecurity surveillance: quantitative approaches, 151–66. Wallingford: CABI, 2015. http://dx.doi.org/10.1079/9781780643595.0151.
Full textSong, Iickho, Jinsoo Bae, and Sun Yong Kim. "Locally Optimum Detection of Known Signals." In Advanced Theory of Signal Detection, 59–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04859-7_2.
Full textSong, Iickho, Jinsoo Bae, and Sun Yong Kim. "Locally Optimum Detection of Random Signals." In Advanced Theory of Signal Detection, 85–121. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04859-7_3.
Full textSong, Iickho, Jinsoo Bae, and Sun Yong Kim. "Locally Optimum Detection of Composite Signals." In Advanced Theory of Signal Detection, 123–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04859-7_4.
Full textKassam, Saleem A. "Optimum Data Quantization in Signal Detection." In Communications and Networks, 72–110. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4904-7_5.
Full textSlobodinskaia, T. V. "The detection probabilities in simultaneous pursuit games." In System Modelling and Optimization, 521–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0035501.
Full textSasaki, Masahide, and Osamu Hirota. "Unitary Control Process for Quantum Optimum Detection." In Quantum Communication, Computing, and Measurement, 269–77. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5923-8_29.
Full textMomose, R., M. Sasaki, and O. Hirota. "Physical Interpretation of Optimum Quantum Detection Operators." In Quantum Communication, Computing, and Measurement, 289–97. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5923-8_31.
Full textConference papers on the topic "The Optimum Detection Probabilities"
Flynn, Eric, and Michael Todd. "Optimal Sensor Placement for Active Sensing." In ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2008. http://dx.doi.org/10.1115/smasis2008-439.
Full textSiewert, Christoph, Rudie P. J. Kunnen, Matthias Meinke, and Wolfgang Schröder. "On the Collision Detection for Ellipsoidal Particles in Turbulence." In ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting collocated with the ASME 2014 12th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/fedsm2014-21982.
Full textBuermann, Jan, and Jie Zhang. "Multi-Robot Adversarial Patrolling Strategies via Lattice Paths." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/582.
Full textSchwall, Matthew L., and J. Christian Gerdes. "Automotive Diagnostic Decisions Using Probabilistic Information." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82169.
Full textLillicrap, D., A. R. Giles, J. J. A. Holden, and B. N. White. "THE RELATIVE EFFICACY OF GENETIC ANALYSIS AND COAGULATION TESTING IN THE DIAGNOSIS OF CARRIERS OF HEMOPHILIA A." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644010.
Full textGoldstein, Adam, and B. Keith Jenkins. "Optical probability density function estimation for real-time pattern classification." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.thq3.
Full textMoritz, Timo, Marc Baumeister, and Thomas Beuker. "Utilization of a Probabilistic Function to Describe the Performance of In-Line Crack Inspection Systems and a Possible Application in Hydrogen Service." In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-87668.
Full textRyan, D. J., I. V. L. Clarkson, and I. B. Collings. "Detection error probabilities in noncoherent channels." In Proceedings. International Symposium on Information Theory, 2005. ISIT 2005. IEEE, 2005. http://dx.doi.org/10.1109/isit.2005.1523409.
Full textKastella, Keith D. "Joint multitarget probabilities for detection and tracking." In AeroSense '97, edited by Michael K. Masten and Larry A. Stockum. SPIE, 1997. http://dx.doi.org/10.1117/12.277194.
Full textBahnsen, Alejandro Correa, Aleksandar Stojanovic, Djamila Aouada, and Björn Ottersten. "Improving Credit Card Fraud Detection with Calibrated Probabilities." In Proceedings of the 2014 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973440.78.
Full textReports on the topic "The Optimum Detection Probabilities"
Ucci, Donald R., William E. Jacklin, and Myron R. Mychal. Robust Locally Optimum Detection. Fort Belvoir, VA: Defense Technical Information Center, July 1996. http://dx.doi.org/10.21236/ada314854.
Full textForrest, R. N. A Program to Compute Electric Anomaly Detection Probabilities. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada201034.
Full textMychal, Myron R., and Donald R. Ucci. Robust Locally Optimum Detection in Auto-Regressive Noise. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada369115.
Full textHill, S. C. Modeling single molecule detection probabilities in microdroplets. Final report. Office of Scientific and Technical Information (OSTI), May 1997. http://dx.doi.org/10.2172/491483.
Full textHill, S. C. Modeling single molecule detection probabilities in microdroplets. Final report. Office of Scientific and Technical Information (OSTI), March 1996. http://dx.doi.org/10.2172/206995.
Full textTardiff, Mark F., Stephen J. Walsh, Kevin K. Anderson, and Lawrence Chilton. Predicting detection probabilities for gas mixtures over HSI backgrounds. Office of Scientific and Technical Information (OSTI), December 2009. http://dx.doi.org/10.2172/1000179.
Full textForrest, R. N. A Program to Compute Magnetic Anomaly Detection Probabilities. Revision 2. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada225427.
Full textPeterson, James T. On the Estimation of Detection Probabilities for Sampling Stream-Dwelling Fishes. Office of Scientific and Technical Information (OSTI), November 1999. http://dx.doi.org/10.2172/783958.
Full textSheen, David M., and Pam M. Aker. Modeling LIDAR Detection of Biological Aerosols to Determine Optimum Implementation Strategy. Office of Scientific and Technical Information (OSTI), September 2007. http://dx.doi.org/10.2172/1074333.
Full textGazze, Chris, Sukesh Aghara, Ian Bleeker, Lohith Annadevula, Ahmad Nofal, Logan Joyce, James Porcello, Katherine Bachner, and Jose Gomera. Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1561261.
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