Literatura académica sobre el tema "Non-stationary distribution"
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Artículos de revistas sobre el tema "Non-stationary distribution"
Kislitsyn, Alexey Alexeevich, Antonina Borisovna Kozlova, Marina Borisovna Korsakova, Evgeniy Leonidovich Masherov y Yurii Nikolaevich Orlov. "Stationary point of significance level for non-stationary distribution functions". Keldysh Institute Preprints, n.º 113 (2018): 1–20. http://dx.doi.org/10.20948/prepr-2018-113.
Texto completoTARASOV, VASILY E. "CLASSICAL CANONICAL DISTRIBUTION FOR DISSIPATIVE SYSTEMS". Modern Physics Letters B 17, n.º 23 (10 de octubre de 2003): 1219–26. http://dx.doi.org/10.1142/s0217984903006268.
Texto completoHesarkazzazi, Sina, Rezgar Arabzadeh, Mohsen Hajibabaei, Wolfgang Rauch, Thomas R. Kjeldsen, Ilaria Prosdocimi, Attilio Castellarin y Robert Sitzenfrei. "Stationary vs non-stationary modelling of flood frequency distribution across northwest England". Hydrological Sciences Journal 66, n.º 4 (12 de marzo de 2021): 729–44. http://dx.doi.org/10.1080/02626667.2021.1884685.
Texto completoFoley, Robert D. "Stationary Poisson departure processes from non-stationary queues". Journal of Applied Probability 23, n.º 1 (marzo de 1986): 256–60. http://dx.doi.org/10.2307/3214138.
Texto completoFoley, Robert D. "Stationary Poisson departure processes from non-stationary queues". Journal of Applied Probability 23, n.º 01 (marzo de 1986): 256–60. http://dx.doi.org/10.1017/s0021900200106497.
Texto completoBehzadi, Mostafa, Mohd Bakri Adam y Anwar Fitrianto. "Univariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto Distribution". Journal of Mathematics and Statistics 13, n.º 2 (1 de febrero de 2017): 169–76. http://dx.doi.org/10.3844/jmssp.2017.169.176.
Texto completoPark, Namuk y Songkuk Kim. "FlexSketch: Estimation of Probability Density for Stationary and Non-Stationary Data Streams". Sensors 21, n.º 4 (4 de febrero de 2021): 1080. http://dx.doi.org/10.3390/s21041080.
Texto completoScala, Pietro, Giuseppe Cipolla, Dario Treppiedi y Leonardo Valerio Noto. "The Use of GAMLSS Framework for a Non-Stationary Frequency Analysis of Annual Runoff Data over a Mediterranean Area". Water 14, n.º 18 (13 de septiembre de 2022): 2848. http://dx.doi.org/10.3390/w14182848.
Texto completoCrisci, Carolina y Gonzalo Perera. "Asymptotic Extremal Distribution for Non-Stationary, Strongly-Dependent Data". Advances in Pure Mathematics 12, n.º 08 (2022): 479–89. http://dx.doi.org/10.4236/apm.2022.128036.
Texto completoGhosh, Ashish y Heinz Muehlenbein. "Univariate marginal distribution algorithms for non-stationary optimization problems". International Journal of Knowledge-based and Intelligent Engineering Systems 8, n.º 3 (10 de enero de 2005): 129–38. http://dx.doi.org/10.3233/kes-2004-8301.
Texto completoTesis sobre el tema "Non-stationary distribution"
Hesarkazzazi, Sina. "Stationary vs. non-stationary modeling of flood frequency distribution across North West England (UK)". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Buscar texto completoRajagopalan, Satish. "Detection of Rotor and Load Faults in BLDC Motors Operating Under Stationary and Non-Stationary Conditions". Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/11524.
Texto completoMuševič, Sašo. "Non-stationary sinusoidal analysis". Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/123809.
Texto completoMany types of everyday signals fall into the non-stationary sinusoids category. A large family of such signals represent audio, including acoustic/electronic, pitched/transient instrument sounds, human speech/singing voice, and a mixture of all: music. Analysis of such signals has been in the focus of the research community for decades. The main reason for such intense focus is the wide applicability of the research achievements to medical, financial and optical applications, as well as radar/sonar signal processing and system analysis. Accurate estimation of sinusoidal parameters is one of the most common digital signal processing tasks and thus represents an indispensable building block of a wide variety of applications. Classic time-frequency transformations are appropriate only for signals with slowly varying amplitude and frequency content - an assumption often violated in practice. In such cases, reduced readability and the presence of artefacts represent a significant problem. Time and frequency resolu
Mamikonyan, Arsen. "Variational inference for non-stationary distributions". Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113125.
Texto completoThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 49).
In this thesis, I look at multiple Variational Inference algorithm, transform Kalman Variational Bayes and Stochastic Variational Inference into streaming algorithms and try to identify if any of them work with non-stationary distributions. I conclude that Kalman Variational Bayes can do as good as any other algorithm for stationary distributions, and tracks non-stationary distributions better than any other algorithm in question.
by Arsen Mamikonyan.
M. Eng.
Jalbert, Jonathan. "Développement d'un modèle statistique non stationnaire et régional pour les précipitations extrêmes simulées par un modèle numérique de climat". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAU032/document.
Texto completoPrecipitation extremes plays a major role in flooding events and their occurrence as well as their intensity are expected to increase. It is therefore important to anticipate the impacts of such an increase to ensure the public safety and the infrastructure sustainability. Since climate models are the only tools for providing quantitative projections of precipitation, flood risk management for the future climate may be based on their simulations. Most of the time, the Extreme value theory is used to estimate the extreme precipitations from a climate simulation, such as the T-year return levels. The variance of the estimations are generally large notably because the sample size of the maxima series are short. Such variance could have a significant impact for flood risk management. It is therefore relevant to reduce the estimation variance of simulated return levels. For this purpose, the aim of this paper is to develop a non-stationary and regional statistical model especially suited for climate models that estimates precipitation extremes. At first, the non-stationarity is removed by a preprocessing approach. Thereafter, the spatial correlation is modeled by a Bayesian hierarchical model including an intrinsic Gaussian Markov random field. The model has been used to estimate the 100-year return levels over North America from a simulation by the Canadian Regional Climate Model. The results show a large estimation variance reduction when using the regional model
Hili, Ouagnina. "Contribution à l'estimation des modèles de séries temporelles non linéaires". Université Louis Pasteur (Strasbourg) (1971-2008), 1995. http://www.theses.fr/1995STR13169.
Texto completoNguyen, Yen Thi Hong. "Time-frequency distributions : approaches for incomplete non-stationary signals". Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/19681/.
Texto completoKinnally, Michael Sean. "Stationary distributions for stochastic delay differential equations with non-negativity constraints". Diss., [La Jolla] : University of California, San Diego, 2009. http://wwwlib.umi.com/cr/ucsd/fullcit?p3355747.
Texto completoTitle from first page of PDF file (viewed June 23, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 114-116).
Fossi, Fotsi Yannick. "Dynamique morpho-sédimentaire de l’estuaire du Wouri, Cameroun". Thesis, La Rochelle, 2022. http://www.theses.fr/2022LAROS012.
Texto completoThe Wouri estuary, located in the heart of the Gulf of Guinea and open to the Atlantic Ocean, is subject to a wide range of atmospheric, oceanic, continental and anthropic influences at different time scales (short and long term) controlling its evolution. The first part of this thesis, based on archives dating back to the 20th century, allows us to reconstruct the history of the evolution of the Wouri estuary coastline. At the same time, in order to determine the evolution trends of the water levels, to quantify and qualify the kinematics of the coastline and the bottoms in the estuary, an inventory, digitization and analysis of historical documents was carried out. This allowed to record an evolution of the average level at a rate of about 25mm/year in 17 years (2002 - 2019). The results revealed a predominance of variations dominated by erosion downstream and conversely by accretion upstream, over the 64-year period (1948-2012). These trends are accentuated by the presence of amplifying factors (anthropogenic pressure and climate change). In order to study the hydrodynamic and sedimentary processes in the short term, a numerical modeling of the tidal propagation and the distribution of salinities and fine sediments was performed using TELEMAC 3D (calibrated and validated thanks to in-situ measurements acquired during 2019). The tide showed an asymmetry dominated by the ebb in its lower part and inversely by the flood in its upper part. The distribution of salinity allowed to characterize the estuary from well mixed in spring tide, particularly in low water to stratified in neap tide, particularly in flood period. Seasonal variations of the river regime have shown a longitudinal migration of the position of the maximum turbidity zone : upstream during low water and downstream during high water with a massive export of sediments in the intermediate and downstream part of the estuary. In a current context of climate change associated with strong anthropogenic impacts, this study highlights the need to use historical archives, in-situ data coupled with a numerical model to better understand the past and present evolution of hydrodynamics and sediment dynamics
RANDAZZO, VINCENZO. "Novel neural approaches to data topology analysis and telemedicine". Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2850610.
Texto completoLibros sobre el tema "Non-stationary distribution"
Coolen, A. C. C., A. Annibale y E. S. Roberts. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0001.
Texto completoTibaldi, Stefano y Franco Molteni. Atmospheric Blocking in Observation and Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.611.
Texto completoCapítulos de libros sobre el tema "Non-stationary distribution"
Cocconcelli, Marco, Radoslaw Zimroz, Riccardo Rubini y Walter Bartelmus. "Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball Bearing Diagnostics". En Condition Monitoring of Machinery in Non-Stationary Operations, 51–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_6.
Texto completoUrbanek, Jacek, Tomasz Barszcz y Jerome Antoni. "Integrated Modulation Intensity Distribution as a Practical Tool for Condition Monitoring – Part 1: Theoretical Investigation". En Condition Monitoring of Machinery in Non-Stationary Operations, 357–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_38.
Texto completoIribarren, Marcelo, Cesar San Martin y Pedro Saavedra. "Processing of Non-Stationary Vibrations Using the Affine Wigner Distribution". En Signal Analysis and Prediction, 89–101. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-1768-8_6.
Texto completoUrbanek, Jacek, Tomasz Barszcz y Jerome Antoni. "Integrated Modulation Intensity Distribution as a Practical Tool for Condition Monitoring – Part 2: Case Study of the Wind Turbine". En Condition Monitoring of Machinery in Non-Stationary Operations, 365–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_39.
Texto completoZhang, Xiangliang y Wei Wang. "Self-adaptive Change Detection in Streaming Data with Non-stationary Distribution". En Advanced Data Mining and Applications, 334–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17316-5_33.
Texto completoKayabol, Koray y Ercan E. Kuruoglu. "Non-stationary t-Distribution Prior for Image Source Separation from Blurred Observations". En Latent Variable Analysis and Signal Separation, 506–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15995-4_63.
Texto completoBojarovich, Julia y Yuliya Dudovskaya. "Stationary Distribution Insensitivity of a Closed Queueing Network with Non-active Customers". En Communications in Computer and Information Science, 50–58. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13671-4_7.
Texto completoBojarovich, Julia y Yury Malinkovsky. "Stationary Distribution Invariance of an Open Queueing Network with Temporarily Non-active Customers". En Communications in Computer and Information Science, 26–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35980-4_4.
Texto completoRouillard, Vincent. "On the Statistical Distribution of Segment Lengths of Road Vehicles Non-Stationary Vibrations". En Experimental Analysis of Nano and Engineering Materials and Structures, 549–50. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-6239-1_272.
Texto completoZhang, Yu, Xiaodong Wang, Zhixiang Min, Shiqiang Wu, Xiufeng Wu, Jiangyu Dai, Fangfang Wang y Ang Gao. "Adaptive Regulation of Cascade Reservoirs System Under Non-stationary Runoff". En Lecture Notes in Civil Engineering, 985–1000. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6138-0_88.
Texto completoActas de conferencias sobre el tema "Non-stationary distribution"
Teyssedre, Gilbert, Thi Thu Nga Vu y Severine Le Roy. "Electric Field Distribution in HVDC Cable Joint in Non-Stationary Conditions". En 2021 IEEE International Conference on the Properties and Applications of Dielectric Materials (ICPADM). IEEE, 2021. http://dx.doi.org/10.1109/icpadm49635.2021.9493863.
Texto completoRaux, Guillaume, Don R. Halverson y Hyeon-Cheol Lee. "Empirical Distribution Approach to the Robustness Measure for Non-stationary Data". En 2007 4th International Symposium on Wireless Communication Systems. IEEE, 2007. http://dx.doi.org/10.1109/iswcs.2007.4392337.
Texto completoFedorov, Sergey, Yurii Orlov, Andrey Samuylov, Dmitri Moltchanov, Yuliya Gaidamaka, Konstantin Samouylov y Sergey Shorgin. "SIR Distribution In D2D Environment With Non-Stationary Mobility Of Users". En 31st Conference on Modelling and Simulation. ECMS, 2017. http://dx.doi.org/10.7148/2017-0720.
Texto completoKarafotis, P. A. y P. S. Georgilakis. "Unbalance and Distortion Evaluation in Three-phase Systems under Non-stationary Conditions". En Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018). Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/cp.2018.1840.
Texto completoNguyen, Yen Thi Hong, Des McLernon, Mounir Ghogho y Ali Zaidi. "Time-Frequency Distribution for Undersampled Non-stationary Signals using Chirp-based Kernel". En 2018 5th NAFOSTED Conference on Information and Computer Science (NICS). IEEE, 2018. http://dx.doi.org/10.1109/nics.2018.8606839.
Texto completoIqbal, Rauf, Thushara Abhayapala, Javed Ahmed y Tharaka Lamahewa. "Wigner-Ville distribution of a type of non-stationary mobile Rayleigh fading channels". En 2009 IEEE 13th International Multitopic Conference (INMIC). IEEE, 2009. http://dx.doi.org/10.1109/inmic.2009.5383132.
Texto completoCondron, J. "Comparison of time-frequency distribution techniques using multi-component non-stationary test signals". En IEE Irish Signals and Systems Conference 2005. IEE, 2005. http://dx.doi.org/10.1049/cp:20050322.
Texto completo"AN INVESTIGATION INTO THE DISTRIBUTION OF MEMBERSHIP GRADES FOR NON-STATIONARY FUZZY SETS". En International Conference on Fuzzy Computation. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002321400790084.
Texto completoLua, James y E. Thomas Mover. "First-Excursion Probability and Response Peak Distribution of a Nonlinear Structure Under Non-Gaussian Non-Stationary Loadings". En ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0392.
Texto completoDe Luca, Davide Luciano, Benedetta Moccia, Fabio Russo y Francesco Napolitano. "Stationary/Non-Stationary Modelling for Extreme Value Distribution: Analysis of Rainfall Annual Maxima in Italy in a Climate Change Context". En EWaS5. Basel Switzerland: MDPI, 2022. http://dx.doi.org/10.3390/environsciproc2022021065.
Texto completoInformes sobre el tema "Non-stationary distribution"
Ho, Hwai-Chung y Tze-Chien Sun. Limiting Distributions of Non-Linear Vector Functions of Stationary Gaussian Processes. Fort Belvoir, VA: Defense Technical Information Center, marzo de 1988. http://dx.doi.org/10.21236/ada194569.
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