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Статті в журналах з теми "Random observations"
Jaynes, E. T. "Some random observations." Synthese 63, no. 1 (April 1985): 115–38. http://dx.doi.org/10.1007/bf00485957.
Повний текст джерелаAndrea, Montanari. "Estimating random variables from random sparse observations." European Transactions on Telecommunications 19, no. 4 (2008): 385–403. http://dx.doi.org/10.1002/ett.1289.
Повний текст джерелаSanandaji, Borhan M., Michael B. Wakin, and Tyrone L. Vincent. "Observability With Random Observations." IEEE Transactions on Automatic Control 59, no. 11 (November 2014): 3002–7. http://dx.doi.org/10.1109/tac.2014.2351693.
Повний текст джерелаO’Neill, Cecily. "Seal Wife – random observations." NJ 41, no. 1 (January 2, 2017): 27–29. http://dx.doi.org/10.1080/14452294.2017.1329687.
Повний текст джерелаSchmidt, Marius, and Rainer Schwabe. "Optimal cutpoints for random observations." Statistics 49, no. 6 (February 17, 2015): 1366–81. http://dx.doi.org/10.1080/02331888.2015.1006225.
Повний текст джерелаWILLIAMS, J. "Random observations on reading research." Issues in Education 5, no. 1 (1999): 161–64. http://dx.doi.org/10.1016/s1080-9724(99)00013-0.
Повний текст джерелаZirbel, Craig L. "Lagrangian observations of homogeneous random environments." Advances in Applied Probability 33, no. 4 (December 2001): 810–35. http://dx.doi.org/10.1239/aap/1011994031.
Повний текст джерелаZirbel, Craig L. "Lagrangian observations of homogeneous random environments." Advances in Applied Probability 33, no. 04 (December 2001): 810–35. http://dx.doi.org/10.1017/s0001867800011216.
Повний текст джерелаCohen, Joel E., and Thomas M. Liggett. "Random arithmetic-geometric means and random pi: observations and conjectures." Stochastic Processes and their Applications 41, no. 2 (June 1992): 261–71. http://dx.doi.org/10.1016/0304-4149(92)90126-b.
Повний текст джерелаEather, Wolfgang, and Matthias Albbecht. "Linear Eegression with Random Fuzzy Observations." Statistics 21, no. 4 (January 1990): 521–31. http://dx.doi.org/10.1080/02331889008802262.
Повний текст джерелаДисертації з теми "Random observations"
Brophy, Edmond M. "Prophet Inequalities for Multivariate Random Variables with Cost for Observations." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1538720/.
Повний текст джерелаMohammed, Hussein Syed. "Random feature subspace ensemble based approaches for the analysis of data with missing features /." Full text available online, 2006. http://www.lib.rowan.edu/find/theses.
Повний текст джерелаRochet, Jean. "Isolated eigenvalues of non Hermitian random matrices." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCB030/document.
Повний текст джерелаThis thesis is about spiked models of non Hermitian random matrices. More specifically, we consider matrices of the type A+P, where the rank of P stays bounded as the dimension goes to infinity and where the matrix A is a non Hermitian random matrix. We first prove that if P has some eigenvalues outside the bulk, then A+P has some eigenvalues (called outliers) away from the bulk. Then, we study the fluctuations of the outliers of A around their limit and prove that they are distributed as the eigenvalues of some finite dimensional random matrices. Such facts had already been noticed for Hermitian models. More surprising facts are that outliers can here have very various rates of convergence to their limits (depending on the Jordan Canonical Form of P) and that some correlations can appear between outliers at a macroscopic distance from each other. The first non Hermitian model studied comes from the Single Ring Theorem due to Guionnet, Krishnapur and Zeitouni. Then we investigated spiked models for nearly Hermitian random matrices : where A is Hermitian but P isn’t. At last, we studied the outliers of Gaussian Elliptic random matrices. This thesis also investigates the convergence in distribution of random variables of the type Tr( f (A)M) where A is a matrix from the Single Ring Theorem and f is analytic on a neighborhood of the bulk and the Frobenius norm of M has order √N. As corollaries, we obtain central limit theorems for linear spectral statistics of A (for analytic test functions) and for finite rank projections of f (A) (like matrix entries)
Alemdar, Meltem. "A Monte Carlo study the impact of missing data in cross-classification random effects models /." Atlanta, Ga. : Georgia State University, 2008. http://digitalarchive.gsu.edu/eps_diss/34/.
Повний текст джерелаTitle from title page (Digital Archive@GSU, viewed July 20, 2010) Carolyn F. Furlow, committee chair; Philo A. Hutcheson, Phillip E. Gagne, Sheryl A. Gowen, committee members. Includes bibliographical references (p. 96-100).
Iufereva, Olga. "Algorithmes de filtrage avec les observations distribuées par Poisson." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. https://theses.hal.science/tel-04720020.
Повний текст джерелаFiltering theory basically relates to optimal state estimation in stochastic dynamical systems, particularly when faced with partial and noisy data. This field, closely intertwined with control theory, focuses on designing estimators doing real-time computation while maintaining an acceptable level of accuracy as measured by the mean square error. The necessity for such estimates becomes increasingly critical with the proliferation of network-controlled systems, such as autonomous vehicles and complex industrial processes, where the observation processes are subject to randomness in transmission and this gives rise to varying information patterns under which the estimation must be carried out.This thesis addresses the important task of state estimation in continuous-time stochastic dynamical systems when the observation process is available only at some discrete time instants governed by a random process. By adapting classical estimation methods, we derive equations for optimal state estimator, explore their properties and practicality, and propose and evaluates sub-optimal alternatives, showcasing parallels to the existing techniques within the classical estimation domain when applied to Poisson-distributed observation processes.The study covers three classes of mathematical models for the continuous-time dynamical system and the discrete observation process. First, we consider Ito-stochastic differential equations with Lipschitz drift terms and constant diffusion coefficient, whereas the lower-dimensional discrete observation process comprises the nonlinear mapping of the state and additive Gaussian noise. We propose easy-to-implement continuous-discrete suboptimal state estimators for this system class. Assuming that a Poisson counter governs discrete times at which the observations are available, we compute the expectation or error covariance process. Analysis is carried out to provide conditions for boundedness of the error covariance process, as well as, the dependence on the mean sampling rate.Secondly, we consider the dynamical systems described by continuous-time Markov chains with finite state space, and the observation process is obtained by discretizing a conventional stochastic process driven by a Wiener process. For this case, the $L_1$-convergence of the derived optimal estimator to the classical (purely continuous) optimal estimator (Wonham filter) is shown with respect to increasing intensity of Poisson processes.Lastly, we study continuous-discrete particle filters for Ornstein-Uhlenbeck processes with discrete observations described by linear functions of state and additive Gaussian noise. Particle filters have gained a lot of interest for state estimation in large-scale models with noisy measurements where the computation of optimal gain is either computationally expensive or not entirely feasible due to complexity of the dynamics. In this thesis, we propose continuous-discrete McKean–Vlasov type diffusion processes, which serve as the mean-field model for describing the particle dynamics. We study several kinds of mean-field processes depending on how the noise terms are included in mimicking the state process and the observation model. The resulting particles are coupled through empirical covariances which are updated at discrete times with the arrival of new observations. With appropriate analysis of the first and second moments, we show that under certain conditions on system parameters, the performance of the particle filters approaches the optimal filter as the number of particles gets larger
Johansson, Åsa M. "Methodology for Handling Missing Data in Nonlinear Mixed Effects Modelling." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-224098.
Повний текст джерелаBourmani, Sabrina. "Binary decision for observations with unknown distribution : an optimal and invariance-based framework." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2020. http://www.theses.fr/2020IMTA0173.
Повний текст джерелаDuring my thesis, we took interest in decision problems where signals are assumed to be stochastic with unknown distributions. In standard literature, such an assumption does not allow to seek solutions that guarantees a certain optimality. At least, aside from the RDT framework developed a few years ago in our laboratory. Hence, we took interest in the philosophy behind the RDT framework, and we follow the same guidelines concerning the unknown distribution of the signal. Apart from our optimality purposes, we also have an invariance based perspective in how we intend to solve this type of decision problems. Indeed, when there are uncertainties about the signal of interest, we can try to derive solutions that are invariant towards them. These are the two key notions we consider throughout our investigations. In this manuscript, first, we apply the RDT framework for a distributed decision to test its suitability to such decision scenarios where the signal of interest is random of unknown distribution and where the observations are collected by a network of sensors instead of just one sensor. Then, we generalise the theoretical material of the RDT framework to when the noise is not necessary Gaussian while still considering the signal of interest random of unknown distribution. Finally, we adopt an asymptotic outlook to circumvent the limitations of the RDT and the developed GRDT approach. Although the considered decision scenarios concern unconditional models in the simple case of deterministic signals, it allows to think ahead of the eventual upcoming generalisations in the asymptotic scope
Martinez, Garcia Alba Maria. "Study of the Resistive Switching Mechanism in Novel Ultra-thin Organic-inorganic Dielectric-based RRAM through Electrical Observations." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299358.
Повний текст джерелаDen senaste introduktionen av ultratunn (<5 nm) organisk-oorganisk hybrid dielektrisk RRAM som nästa generations icke-flyktiga minnesenheter kräver en djup förståelse för hybridskiktresistiv växling (RS). Den extremt reducerade tjockleken hindrar emellertid deras bearbetbarhet för materialkarakteriseringstekniker. Dessutom hindrar den dåliga enhetligheten i viktiga omkopplingsparametrar fortfarande i RRAM att alla trender kan definieras tydligt genom elektrisk karakterisering. Detta arbete använder elektrisk manipulation genom en RPS-metod (ramped-pulse series) för att förbättra spännings- och motståndsfluktuationerna i återställningsprocessen för ultratunna Al/Hf-hybrid/Ni-enheter vid olika spänningsamplitud, pulsbredd och temperaturförhållanden. Från de erhållna RPS-optimerade resultaten föreslås en ny och detaljerad fysisk modell som beskriver driftsmekanismen. Samexistensen i den ledande filamenten (CF) av en hybridmetalldel, sammansatt av Al och Hf3Al2, och en syrevakansdel bekräftas. Vår modell betonar vakansbidraget i RS, där majoriteten genereras under CF-formningsprocessen och deltar i olika grad i filamentbrottet för RPS och ingen RPS-bearbetade enheter via Joule-uppvärmning, drift och Fick-krafter. Dessutom förklaras kopplingsfelhändelser baserat på närvaron av ett Al2O3-lager i Al/Hf-hybridgränssnittet.
Wabiri, Njeri. "Variable modeling of spatially distributed random interval observation." Doctoral thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/4365.
Повний текст джерелаArrowood, Jon A. "Using observation uncertainty for robust speech recognition." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180005/unrestricted/arrowood%5Fjon%5Fa%5F200312%5Fphd.pdf.
Повний текст джерелаКниги з теми "Random observations"
University, Emory, ed. I have never tasted any bad ice cream and other random observations. Decatur, G.A: Looking Glass Books, 1997.
Знайти повний текст джерелаWeinberg, Israel Louis. Settings at random: Observations, experiences, ideas : Brick Lane, London E1, 1915-1987. [Wembley] (]28, Blenheim Gardens, East Lane, Wembley, HA9 7NP]): [I.L. Weinberg], 1987.
Знайти повний текст джерелаHyde, Henry J. Catch the burning flag: Speeches and random observations of Henry Hyde ; [foreword by Robert Novak]. New York: National Review Books, 2008.
Знайти повний текст джерелаNäther, Wolfgang. Effective observation of random fields. Leipzig: Teubner, 1985.
Знайти повний текст джерелаDavies, Merton E. Rand's role in the evolution of balloon and satellite observation systems and related U.S. space technology. Santa Monica, CA: Rand Corp., 1988.
Знайти повний текст джерелаShort, Nevil. Random Observations. Unknown Publisher, 2021.
Знайти повний текст джерелаRichard, Smith. Random Observations. Certainty Perspectives, 2020.
Знайти повний текст джерелаMaready, Kenan. Random Thoughts and Observations. Independently Published, 2019.
Знайти повний текст джерелаMcWhorter, Jenn. Random Rants and Other Observations. Lulu Press, Inc., 2008.
Знайти повний текст джерелаSingle Exposures (Random Observations on Photography, Art & Creativity). LensWork Publishing, 2005.
Знайти повний текст джерелаЧастини книг з теми "Random observations"
Azencott, Robert, and Didier Dacunha-Castelle. "Discrete Time Random Processes." In Series of Irregular Observations, 3–9. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4912-2_2.
Повний текст джерелаAzencott, Robert, and Didier Dacunha-Castelle. "Random Fields and Stochastic Integrals." In Series of Irregular Observations, 37–45. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4912-2_6.
Повний текст джерелаNäther, Wolfgang, and Ralf Körner. "Linear regression with random fuzzy observations." In Statistical Modeling, Analysis and Management of Fuzzy Data, 282–305. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1800-0_18.
Повний текст джерелаMorales, Domingo, Leandro Pardo, and Igor Vajda. "Digitalization of Observations Permits Efficient Estimation in Continuous Models." In Soft Methodology and Random Information Systems, 315–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-44465-7_38.
Повний текст джерелаSabre, Rachid. "Evolutionary Spectrum for Random Field and Missing Observations." In Lecture Notes in Computer Science, 209–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31254-0_24.
Повний текст джерелаGouet, Raúl, Miguel Lafuente, F. Javier López, and Gerardo Sanz. "$$\delta $$ δ -Records Observations in Models with Random Trend." In Studies in Systems, Decision and Control, 209–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73848-2_20.
Повний текст джерелаChazelle, Bernard. "Some Observations on Dynamic Random Walks and Network Renormalization." In Fundamentals of Computation Theory, 18–28. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25027-0_2.
Повний текст джерелаWalrand, Jean. "Tracking—A." In Probability in Electrical Engineering and Computer Science, 163–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_9.
Повний текст джерелаBadings, Thom, Matthias Volk, Sebastian Junges, Marielle Stoelinga, and Nils Jansen. "CTMCs with Imprecisely Timed Observations." In Tools and Algorithms for the Construction and Analysis of Systems, 258–78. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57249-4_13.
Повний текст джерелаWei, Zheng, Tonghui Wang, and Baokun Li. "On Consistency of Estimators Based on Random Set Vector Observations." In Causal Inference in Econometrics, 185–98. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27284-9_11.
Повний текст джерелаТези доповідей конференцій з теми "Random observations"
Prasad, J. V. R., Vinodhini Comandur, Robert Walters, and David Guerrero. "Model Predictive Path Integral Approach for Trajectory Guidance of Rotorcraft Shipboard Landing." In Vertical Flight Society 80th Annual Forum & Technology Display, 1–16. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0074-2018-12780.
Повний текст джерелаJie, Zhang, Lu Huiguo, and Luo Yangyi. "Spatial Consistency Test Method for Meteorological Data Based On Random Forest." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9026034.
Повний текст джерелаZafarani, Reza, and Ali A. Ghorbani. "Oracle Clustering: Dynamic Partitioning Based on Random Observations." In 2008 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2008. http://dx.doi.org/10.1109/ictai.2008.128.
Повний текст джерелаHuang, Wubin, Yingsha Jiang, Xinwei Liu, Yongjie Pan, Xia Li, Runxia Guo, Yuxia Huang, and Bolong Duan. "Classified Early-warning and Nowcasting of Hail Weather Based on Radar Products and Random Forest Algorithm." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9026039.
Повний текст джерелаXu, Kaiqin, Zhijian Cai, and Jianhong Wu. "Random pixelated grating computational spectrometer based on deep learning." In Conference on Novel Technologies and Instruments for Astronomical Multi-Band Observations, edited by Suijian Xue and Yongtian Zhu. SPIE, 2021. http://dx.doi.org/10.1117/12.2607021.
Повний текст джерелаBoldyrikhin, Nikolay V., Olga A. Safaryan, and Alexey A. Svizhenko. "Optimization of Observations for a Limited Flow of Random Processes." In 2021 Radiation and Scattering of Electromagnetic Waves (RSEMW). IEEE, 2021. http://dx.doi.org/10.1109/rsemw52378.2021.9494057.
Повний текст джерелаJiang, Fan, Yu Ge, Meifang Zhu, Henk Wymeersch, and Fredrik Tufvesson. "Low-Complexity Channel Estimation and Localization with Random Beamspace Observations." In ICC 2023 - IEEE International Conference on Communications. IEEE, 2023. http://dx.doi.org/10.1109/icc45041.2023.10278994.
Повний текст джерелаReiffers-Masson, Alexandre, Thierry Chonavel, and Yezekael Hayel. "Estimating Fiedler Value on Large Networks Based on Random Walk Observations." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413713.
Повний текст джерелаSoucie, John E. San, Heidi M. Sosik, and Yogesh Girdhar. "Gaussian-Dirichlet Random Fields for Inference over High Dimensional Categorical Observations." In 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020. http://dx.doi.org/10.1109/icra40945.2020.9196713.
Повний текст джерелаPalafox, Leon, Laszlo A. Jeni, and Hideki Hashimoto. "Using conditional random fields to validate observations in a 4W1H paradigm." In 2011 4th International Conference on Human System Interactions (HSI). IEEE, 2011. http://dx.doi.org/10.1109/hsi.2011.5937347.
Повний текст джерелаЗвіти організацій з теми "Random observations"
Bucklew, James A., and Stamatis Cambanis. Estimating Random Integrals from Noisy Observations: Sampling Designs and Their Performance. Fort Belvoir, VA: Defense Technical Information Center, December 1985. http://dx.doi.org/10.21236/ada170330.
Повний текст джерелаBlake, J. B., and R. Mandel. On-Orbit Observations of Single-Event Upset in Harris HM-6508 RAMSs (Random Access Memories): An Update. Fort Belvoir, VA: Defense Technical Information Center, February 1989. http://dx.doi.org/10.21236/ada206266.
Повний текст джерелаShiller, Robert, and Pierre Perron. Testing the Random Walk Hypothesis: Power versus Frequency of Observation. Cambridge, MA: National Bureau of Economic Research, April 1985. http://dx.doi.org/10.3386/t0045.
Повний текст джерелаAraujo, María Caridad, Yyannu Cruz-Aguayo, Pedro Carneiro, and Norbert Schady. Teacher Quality and Learning Outcomes in Kindergarten. Inter-American Development Bank, December 2016. http://dx.doi.org/10.18235/0011718.
Повний текст джерелаAsenath-Smith, Emily, Ross Lieblappen, Susan Taylor, Reed Winter, Terry Melendy, Robert Moser, and Robert Haehnel. Observation of crack arrest in ice by high aspect ratio particles during uniaxial compression. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43145.
Повний текст джерелаBäumler, Maximilian, Günther Prokop, Matthias Lehmann, and Linda Dziuba-Kaiser. Use Information You Have Never Observed Together: Data Fusion as a Major Step Towards Realistic Test Scenarios. TU Dresden, 2020. http://dx.doi.org/10.26128/2024.3.
Повний текст джерелаGupta, Tejpal, Riddhijyoti Talukdar, Sadhana Kannan, Archya Dasgupta, Abhishek Chatterjee, and Vijay Patil. Meta-Analysis of Standard Temozolomide versus Extended Adjuvant Temozolomide following concurrent Radiochemotherapy in newly-diagnosed Glioblastoma (MASTER-G). INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2021. http://dx.doi.org/10.37766/inplasy2021.12.0114.
Повний текст джерелаEldar, Avigdor, and Donald L. Evans. Streptococcus iniae Infections in Trout and Tilapia: Host-Pathogen Interactions, the Immune Response Toward the Pathogen and Vaccine Formulation. United States Department of Agriculture, December 2000. http://dx.doi.org/10.32747/2000.7575286.bard.
Повний текст джерелаSprague, Joshua, David Kushner, James Grunden, Jamie McClain, Benjamin Grime, and Cullen Molitor. Channel Islands National Park Kelp Forest Monitoring Program: Annual report 2014. National Park Service, August 2022. http://dx.doi.org/10.36967/2293855.
Повний текст джерелаWeissinger, Rebecca. Evaluation of hanging-garden endemic-plant monitoring at Southeast Utah Group national parks, 2013–2020. Edited by Alice Wondrak Biel. National Park Service, October 2022. http://dx.doi.org/10.36967/2294868.
Повний текст джерела