Bibliografías temáticas / Stochastic analysis

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Literatura académica sobre el tema "Stochastic analysis"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 25 de julio de 2025

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Artículos de revistas sobre el tema "Stochastic analysis"

1

PE and P. Malliavin. "Stochastic Analysis." Journal of the American Statistical Association 93, no. 441 (1998): 411. http://dx.doi.org/10.2307/2669659.

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Hu, Peng, та Chengming Huang. "The StochasticΘ-Method for Nonlinear Stochastic Volterra Integro-Differential Equations". Abstract and Applied Analysis 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/583930.

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The stochasticΘ-method is extended to solve nonlinear stochastic Volterra integro-differential equations. The mean-square convergence and asymptotic stability of the method are studied. First, we prove that the stochasticΘ-method is convergent of order1/2in mean-square sense for such equations. Then, a sufficient condition for mean-square exponential stability of the true solution is given. Under this condition, it is shown that the stochasticΘ-method is mean-square asymptotically stable for every stepsize if1/2≤θ≤1and when0≤θ<1/2, the stochasticΘ-method is mean-square asymptotically stable
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Markus, L., and A. Weerasinghe. "Stochastic oscillators." Journal of Differential Equations 71, no. 2 (1988): 288–314. http://dx.doi.org/10.1016/0022-0396(88)90029-0.

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Sankar, T. S., S. A. Ramu, and R. Ganesan. "Stochastic Finite Element Analysis for High Speed Rotors." Journal of Vibration and Acoustics 115, no. 1 (1993): 59–64. http://dx.doi.org/10.1115/1.2930315.

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The general problem of the dynamic response of highspeed rotors is considered in which certain system parameters may have a spatial stochastic variation. In particular the elastic modulus and mass density of a rotating shaft are described through one dimensional stochastic field functions so that the imperfections in manufacture and measurement can be accounted for. The stochastic finite element method is developed so that the variability of the response of the rotor can be interpreted in terms of the variation of the material property. As an illustration the whirl speed analysis is performed
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Zhao, Wenqiang, and Yangrong Li. "Existence of Random Attractors for ap-Laplacian-Type Equation with Additive Noise." Abstract and Applied Analysis 2011 (2011): 1–21. http://dx.doi.org/10.1155/2011/616451.

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We first establish the existence and uniqueness of a solution for a stochasticp-Laplacian-type equation with additive white noise and show that the unique solution generates a stochastic dynamical system. By using the Dirichlet forms of Laplacian and an approximation procedure, the nonlinear obstacle, arising from the additive noise is overcome when we make energy estimate. Then, we obtain a random attractor for this stochastic dynamical system. Finally, under a restrictive assumption on the monotonicity coefficient, we find that the random attractor consists of a single point, and therefore t
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Hengki, Tamando Sihotang, Efendi Syahril, Zarlis Muhammad, and Mawengkang Herman. "Data driven approach for stochastic data envelopment analysis." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1497~1504. https://doi.org/10.11591/eei.v11i3.3660.

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Decision making based on data driven deals with a large amount of data will evaluate the process's effectiveness. Evaluate effectiveness in this paper is measure of performance efficiency of data envelopment analysis (DEA) method in this study is the approach with uncertainty problems. This study proposed a new method called the robust stochastic DEA (RSDEA) to approach performance efficiency in tackling uncertainty problems (i.e., stochastic and robust optimization). The RSDEA method develops to combine the stochastics DEA (SDEA) formulation method and Robust Optimization. The numerical e
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IMKELLER, PETER, and ADAM HUGH MONAHAN. "CONCEPTUAL STOCHASTIC CLIMATE MODELS." Stochastics and Dynamics 02, no. 03 (2002): 311–26. http://dx.doi.org/10.1142/s0219493702000443.

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From July 9 to 11, 2001, 50 researchers from the fields of climate dynamics and stochastic analysis met in Chorin, Germany, to discuss the idea of stochastic models of climate. The present issue of Stochastics and Dynamics collects several papers from this meeting. In this introduction to the volume, the idea of simple conceptual stochastic climate models is introduced amd recent results in the mathematically rigorous development and analysis of such models are reviewed. As well, a brief overview of the application of ideas from stochastic dynamics to simple models of the climate system is giv
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Ocone, Daniel. "Stochastic calculus of variations for stochastic partial differential equations." Journal of Functional Analysis 79, no. 2 (1988): 288–331. http://dx.doi.org/10.1016/0022-1236(88)90015-8.

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Sihotang, Hengki Tamando, Syahril Efendi, Muhammad Zarlis, and Herman Mawengkang. "Data driven approach for stochastic data envelopment analysis." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1497–504. http://dx.doi.org/10.11591/eei.v11i3.3660.

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Decision making based on data driven deals with a large amount of data will evaluate the process's effectiveness. Evaluate effectiveness in this paper is measure of performance efficiency of data envelopment analysis (DEA) method in this study is the approach with uncertainty problems. This study proposed a new method called the robust stochastic DEA (RSDEA) to approach performance efficiency in tackling uncertainty problems (i.e., stochastic and robust optimization). The RSDEA method develops to combine the stochastics DEA (SDEA) formulation method and Robust Optimization. The numerical examp
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OGURA, Yukio. "Stochastic Fuzzy Analysis." Journal of Japan Society for Fuzzy Theory and Systems 10, no. 6 (1998): 1012–19. http://dx.doi.org/10.3156/jfuzzy.10.6_1012.

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Tesis sobre el tema "Stochastic analysis"

1

Yang, Weiye. "Stochastic analysis and stochastic PDEs on fractals." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:43a7af74-c531-424a-9f3d-4277138affbb.

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Stochastic analysis on fractals is, as one might expect, a subfield of analysis on fractals. An intuitive starting point is to observe that on many fractals, one can define diffusion processes whose law is in some sense invariant with respect to the symmetries and self-similarities of the fractal. These can be interpreted as fractal-valued counterparts of standard Brownian motion on Rd. One can study these diffusions directly, for example by computing heat kernel and hitting time estimates. On the other hand, by associating the infinitesimal generator of the fractal-valued diffusion with the L
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Ozkan, Pelin. "Analysis Of Stochastic And Non-stochastic Volatility Models." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605421/index.pdf.

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Changing in variance or volatility with time can be modeled as deterministic by using autoregressive conditional heteroscedastic (ARCH) type models, or as stochastic by using stochastic volatility (SV) models. This study compares these two kinds of models which are estimated on Turkish / USA exchange rate data. First, a GARCH(1,1) model is fitted to the data by using the package E-views and then a Bayesian estimation procedure is used for estimating an appropriate SV model with the help of Ox code. In order to compare these models, the LR test statistic calculated for non-nested hypotheses is
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Binotto, Giulia. "Contributions to stochastic analysis." Doctoral thesis, Universitat de Barcelona, 2018. http://hdl.handle.net/10803/565571.

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The aim of this dissertation is to present some new results on stochastic analysis. It consists on three works that deal with two Gaussian processes: the Brownian motion and the fractional Brownian motion with Hurst parameter H less than 1/2. In the first work we construct a family of processes, from a single Poisson process and a sequence of independent random variables with common Bernoulli distribution, that converges in law to a complex Brownian motion. We find realizations of these processes that converge almost surely to the complex Brownian motion, uniformly on the unit time interval
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Davies, M. J. "Topics in stochastic analysis." Thesis, Swansea University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.636421.

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This thesis uses Nelson's stochastic mechanics to study a variety of problems. These include point sources, particles in a constant magnetic field with oscillator potentials and Brownian Motion with a constant drift. By using a finite difference approximation Chapter 1 gives an account of the Stochastic Variational Principle for stochastic mechanics based on Carlen's approach. It is shown that every diffusion satisfying the dynamical law of stochastic mechanics corresponds to a solution of the Schröinger equation. Chapter 2 is concerned with point sources and gives a brief account of Nelson's
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Nadakuditi, Rajesh Rao. "Applied stochastic Eigen-analysis." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38538.

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Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2006.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Also issued in pages. Barker Engineering Library copy: issued in pages.<br>Includes bibliographical references (leaves 193-[201]).<br>The first part of the dissertation investigates the application of the theory of large random
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Liu, Xuan. "Some contribution to analysis and stochastic analysis." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:485474c0-2501-4ef0-a0bc-492e5c6c9d62.

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The dissertation consists of two parts. The first part (Chapter 1 to 4) is on some contributions to the development of a non-linear analysis on the quintessential fractal set Sierpinski gasket and its probabilistic interpretation. The second part (Chapter 5) is on the asymptotic tail decays for suprema of stochastic processes satisfying certain conditional increment controls. Chapters 1, 2 and 3 are devoted to the establishment of a theory of backward problems for non-linear stochastic differential equations on the gasket, and to derive a probabilistic representation to some parabolic type par
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7

Johannessen, Knut. "Stochastic analysis of Workover Risers." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11550.

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The goal of this thesis is to investigate the properties of dynamic analysis of slender, top tensioned risers when using both regular and irregular waves. The goal was to discover properties in the response that correlates to a parameter that can be found in both methods. The approach is to use a model of a riser in open water connected to the sea bed, and top tensioned by a semi submersible rig subjected to the dynamic load of waves and currents. The theories that hold the basis of dynamic analyses using finite elements are outlined, and different methods of solving the dynamic equilibrium eq
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Youssef, Nataly. "Stochastic analysis via robust optimization." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103246.

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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2016.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 167-174).<br>To evaluate the performance and optimize systems under uncertainty, two main avenues have been suggested in the literature: stochastic analysis and optimization describing the uncertainty probabilistically and robust optimization describing the uncertainty deterministically. Instead, we propose a novel paradigm which leverages the conclusions of probability theor
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Whiteside, M. B. "Stochastic analysis of composite materials." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/9986.

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This thesis describes the development of stochastic analysis frameworks for use in engineering design and optimisation. The research focuses on fibre-reinforced composites, with the stochastic analyses of an existing analytical failure model for unidirectional composites and of a unit cell numerical model of a 2D 5-Harness satin weave. Stochastic failure envelopes are generated through parallelised Monte Carlo Simulation of deterministic, analytical, physically based failure criteria for unidirectional carbon fibre/epoxy matrix composite plies. Monte Carlo integration of global variance-based
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Güngör, Mesut Savacı Ferit Acar. "Analysis of Stochastic Dynamical Systems/." [s.l.]: [s.n.], 2007. http://library.iyte.edu.tr/tezler/master/elektrikveelektronikmuh/T000630.pdf.

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Libros sobre el tema "Stochastic analysis"

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Métivier, Michel, and Shinzo Watanabe, eds. Stochastic Analysis. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0077861.

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Cranston, Michael, and Mark Pinsky, eds. Stochastic Analysis. American Mathematical Society, 1994. http://dx.doi.org/10.1090/pspum/057.

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Kusuoka, Shigeo. Stochastic Analysis. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8864-8.

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Malliavin, Paul. Stochastic Analysis. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-15074-6.

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Malliavin, Paul. Stochastic analysis. Springer, 1997.

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Karatzas, Ioannis, and Daniel Ocone, eds. Applied Stochastic Analysis. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/bfb0007043.

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Crisan, Dan, ed. Stochastic Analysis 2010. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15358-7.

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A, Davis M. H., and Elliott Robert J. 1940-, eds. Applied stochastic analysis. Gordon and Breach Science Publishers, 1991.

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A, Davis M. H., and Elliott R. J, eds. Applied stochastic analysis. Gordon and Breach, 1990.

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service), SpringerLink (Online, ed. Stochastic Analysis 2010. Springer-Verlag Berlin Heidelberg, 2011.

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Capítulos de libros sobre el tema "Stochastic analysis"

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Osswald, Horst. "Stochastic Analysis." In Nonstandard Analysis for the Working Mathematician. Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-7327-0_7.

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Hacιsalihzade, Selim S. "Stochastic Analysis." In Control Engineering and Finance. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64492-9_5.

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Natale, Marco Di, Haibo Zeng, Paolo Giusto, and Arkadeb Ghosal. "Stochastic Analysis." In Understanding and Using the Controller Area Network Communication Protocol. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0314-2_4.

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Ganguli, Ranjan, Sondipon Adhikari, Souvik Chakraborty, and Mrittika Ganguli. "Stochastic Analysis." In Digital Twin. CRC Press, 2023. http://dx.doi.org/10.1201/9781003268048-4.

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Karim, Md Rezaul, and M. Ataharul Islam. "Stochastic Models." In Reliability and Survival Analysis. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9776-9_11.

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Hu, Shouchuan, and Nikolas S. Papageorgiou. "Stochastic Games." In Handbook of Multivalued Analysis. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4665-8_7.

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Wen, Meilin. "Stochastic DEA." In Uncertain Data Envelopment Analysis. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43802-2_3.

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Söderström, T. "Analysis." In Discrete-time Stochastic Systems. Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0101-7_4.

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Jacob, Christian. "Stochastic Search Methods." In Intelligent Data Analysis. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03969-4_9.

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Au, Siu-Kui. "Stochastic Structural Dynamics." In Operational Modal Analysis. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4118-1_5.

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Actas de conferencias sobre el tema "Stochastic analysis"

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Jiang, Shanshan, Lijin Wang, and Jialin Hong. "Stochastic multisymplectic integrator for stochastic KdV equation." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756515.

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"Stochastic analysis." In Proceedings of the 7th International ISAAC Congress. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814313179_others10.

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Kanniainen, Juho. "Cause of Stock Return Stochastic Volatility: Query by Way of Stochastic Calculus." In Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0003.

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Ekhaguere, G. O. S. "Contemporary Stochastic Analysis." In International Conference on Contemporary Problems in Stochastic Analysis and its Applications. WORLD SCIENTIFIC, 1991. http://dx.doi.org/10.1142/9789814538756.

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Negrea, Romeo. "On a class of backward stochastic differential equations and applications to the stochastic resonance." In Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0004.

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Hong, Jialin, and Lihai Ji. "Stochastic multi-symplectic wavelet collocation method for stochastic Hamiltonian Maxwell's equations." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756514.

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P., Spanos, Pirrotta A., Marino F., and Robledo Ricardo L. A. "Stochastic Analysis of Motorcycle Dynamics." In 6th International Conference on Computational Stochastic Mechanics. Research Publishing Services, 2011. http://dx.doi.org/10.3850/978-981-08-7619-7_p056.

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Juuti, Mika, Francesco Corona, and Juha Karhunen. "Stochastic Discriminant Analysis." In 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, 2015. http://dx.doi.org/10.1109/ijcnn.2015.7280609.

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Pettere, Gaida. "Stochastic Risk Capital Model for Insurance Company." In Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0014.

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Wisniewski, Rafael, and Manuela L. Bujorianu. "Stochastic safety analysis of stochastic hybrid systems." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263999.

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Informes sobre el tema "Stochastic analysis"

1

Cawlfield, J. D. Stochastic analysis of contaminant transport. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/5827751.

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Budhiraja, Amarjit. Stochastic Analysis and Applied Probability(3.3.1): Topics in the Theory and Applications of Stochastic Analysis. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada625850.

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HEY, B. E. Stochastic Consequence Analysis for Waste Leaks. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/803657.

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Johnson, Ralph. Stochastic Simulation Analysis - 2005 (SSA-05). Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada329429.

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Mathew, George A., and Alessandro Pinto. Stochastic Analysis and Design of Systems. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada552645.

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Heifets, Samuel A. Quantum-mechanical Analysis of Optical Stochastic Cooling. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/784790.

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Heifets, Samuel A. Quantum-mechanical Analysis of Optical Stochastic Cooling. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/784820.

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Dshalalow, Jewgeni H. Random Walk Analysis in Antagonistic Stochastic Games. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada533481.

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Foes, Chamberlain. A study an analysis of stochastic linear programming. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.821.

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Ghassemi, Ahmad. Geomechanics-Based Stochastic Analysis of Injection- Induced Seismicity. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1375732.

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