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Relevant bibliographies by topics / Generalized stochastic processes

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Academic literature on the topic 'Generalized stochastic processes'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Generalized stochastic processes"

1

Mirkov, Radoslava, Stevan Pilipović, and Dora Seleši. "Generalized stochastic processes in algebras of generalized functions." Journal of Mathematical Analysis and Applications 353, no. 1 (2009): 260–70. http://dx.doi.org/10.1016/j.jmaa.2008.11.065.

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Dévoué, Victor. "Some Nonlinear Stochastic Cauchy Problems with Generalized Stochastic Processes." International Journal of Analysis 2016 (October 18, 2016): 1–11. http://dx.doi.org/10.1155/2016/5963420.

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We study some nonlinear stochastic Cauchy problems in the framework of the (C,E,P)-algebras. We adapt the definitions to this framework. By means of suitable regularizations, we define associated generalized problems. We use our previous results about the wave equation in canonical form to obtain generalized solutions. We compare the generalized solutions with the classical ones when they exist.

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Alghalith, Moawia. "Generalized Stochastic Processes: The Portfolio Model." Journal of Mathematical Finance 02, no. 02 (2012): 199–201. http://dx.doi.org/10.4236/jmf.2012.22022.

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Müller, Bernd. "On generalized quantum stochastic counting processes." Communications in Mathematical Physics 173, no. 3 (1995): 453–74. http://dx.doi.org/10.1007/bf02101654.

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NEDELJKOV, MARKO, and DANIJELA RAJTER. "NONLINEAR STOCHASTIC WAVE EQUATION WITH COLOMBEAU GENERALIZED STOCHASTIC PROCESSES." Mathematical Models and Methods in Applied Sciences 12, no. 05 (2002): 665–88. http://dx.doi.org/10.1142/s0218202502001842.

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Colombeau generalized stochastic processes are introduced in order to solve nonlinear wave and Klein–Gordon equations with stochastic processes. Particular cases include one- and three-dimensional wave and Klein–Gordon equations with Lipschitz and cubic nonlinearities. In all cases, considered as Colombeau generalized stochastic processes, solutions are obtained and proved to be unique. The normalizations of the initial data and stochastic processes appear to be the crucial points for the existence of solutions to the above equations.

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Valenti, D., O. A. Chichigina, A. A. Dubkov, and B. Spagnolo. "Stochastic acceleration in generalized squared Bessel processes." Journal of Statistical Mechanics: Theory and Experiment 2015, no. 2 (2015): P02012. http://dx.doi.org/10.1088/1742-5468/2015/02/p02012.

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Cha, Ji Hwan. "Stochastic comparison of generalized combined risk processes." Journal of Statistical Planning and Inference 143, no. 4 (2013): 818–26. http://dx.doi.org/10.1016/j.jspi.2012.10.012.

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Obata, Nobuaki. "Generalized quantum stochastic processes on Fock space." Publications of the Research Institute for Mathematical Sciences 31, no. 4 (1995): 667–702. http://dx.doi.org/10.2977/prims/1195163920.

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Karpenko, V. A. "Linear prediction for generalized oscillating stochastic processes." Computational Mathematics and Modeling 5, no. 2 (1994): 189–94. http://dx.doi.org/10.1007/bf01130287.

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Seleši, Dora. "Algebra of Generalized Stochastic Processes and the Stochastic Dirichlet Problem." Stochastic Analysis and Applications 26, no. 5 (2008): 978–99. http://dx.doi.org/10.1080/07362990802286053.

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Dissertations / Theses on the topic "Generalized stochastic processes"

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Snežana, Gordić. "Generalized stochastic processes with applications in equation solving." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2019. https://www.cris.uns.ac.rs/record.jsf?recordId=110199&source=NDLTD&language=en.

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In this dissertation stochastic processes are regarded in the framework of Colombeau-type algebras of generalized functions. Such processes are called Colombeau stochastic processes.The notion of point values of Colombeau stochastic processes in compactly supported generalized points is established. The Colombeau algebra of compactly supported generalized constants is endowed with the topology generated by sharp open balls. The measurability of the corresponding random variables with values in the Colombeau algebra of compactly supported generalized constants is shown.The generalized correlati

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Das, Suman. "Orthogonal decompositions for generalized stochastic processes with independent values." Thesis, Swansea University, 2013. https://cronfa.swan.ac.uk/Record/cronfa42660.

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Among all stochastic processes with independent increments, essentially only Brownian motion and Poisson process have a chaotic representation property. In the case of a Levy process, several approaches have been proposed in order to construct an orthogonal decomposition of the corresponding L2-space. In this dissertation, we deal with orthogonal (chaotic) decompositions for generalized processes with independent values. We do not suppose stationarity of the process, as a result the Levy measure of the process depends on points of the space. We first construct, in Chapter 3, a unitary isomorph

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Yam, Ho-kwan, and 任浩君. "On a topic of generalized linear mixed models and stochastic volatility model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B29913342.

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Messerschmidt, Reinhardt. "Hattendorff’s theorem and Thiele’s differential equation generalized." Diss., University of Pretoria, 2005. http://hdl.handle.net/2263/30476.

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Hattendorff's theorem on the zero means and uncorrelatedness of losses in disjoint time periods on a life insurance policy is derived for payment streams, discount functions and time periods that are all stochastic. Thiele's differential equation, describing the development of life insurance policy reserves over the contract period, is derived for stochastic payment streams generated by point processes with intensities. The development follows that by Norberg. In pursuit of these aims, the basic properties of Lebesgue-Stieltjes integration are spelled out in detail. An axiomatic approach to th

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Fan, Futing. "Improving GEMFsim: a stochastic simulator for the generalized epidemic modeling framework." Kansas State University, 2016. http://hdl.handle.net/2097/34564.

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Master of Science<br>Department of Electrical and Computer Engineering<br>Caterina M. Scoglio<br>The generalized epidemic modeling framework simulator (GEMFsim) is a tool designed by Dr. Faryad Sahneh, former PhD student in the NetSE group. GEMFsim simulates stochastic spreading process over complex networks. It was first introduced in Dr. Sahneh’s doctoral dissertation "Spreading processes over multilayer and interconnected networks" and implemented in Matlab. As limited by Matlab language, this implementation typically solves only small networks; the slow simulation speed is unable to genera

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Otunuga, Olusegun Michael. "Stochastic Modeling and Analysis of Energy Commodity Spot Price Processes." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5289.

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Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand expectation process. In order to be able to understand the price balancing process, it is important to know the economic forces and the behavior of energy commodity spot price processes. The relationship between the different energy sources and its utility together with uncertainty also play a role in many important energy issues. The qualitative and quantitative behavior of energy commodities in which the trend in price of one com

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Xiaochen, Liu. "Statistical Analysis of Integrated Circuits Using Decoupled Polynomial Chaos." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34836.

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One of the major tasks in electronic circuit design is the ability to predict the performance of general circuits in the presence of uncertainty in key design parameters. In the mathematical literature, such a task is referred to as uncertainty quantification. Uncertainty about the key design parameters arises mainly from the difficulty of controlling the physical or geometrical features of the underlying design, especially at the nanometer level. With the constant trend to scale down the process feature size, uncertainty quantification becomes crucial in shortening the design time. To achieve

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Lara, Idemauro Antonio Rodrigues de. "Modelos de transição para dados binários." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-04122007-102643/.

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Dados binários ou dicotômicos são comuns em muitas áreas das ciências, nas quais, muitas vezes, há interesse em registrar a ocorrência, ou não, de um evento particular. Por outro lado, quando cada unidade amostral é avaliada em mais de uma ocasião no tempo, tem-se dados longitudinais ou medidas repetidas no tempo. é comum também, nesses estudos, se ter uma ou mais variáveis explicativas associadas às variáveis respostas. As variáveis explicativas podem ser dependentes ou independentes do tempo. Na literatura, há técnicas disponíveis para a modelagem e análise desses dados, sendo os modelos dis

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Choi, Jin Young. "Performance Modeling, Analysis and Control of Capacitated Re-entrant Lines." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5032.

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This thesis considers the problem of performance modeling, analysis and control of capacitated re-entrant lines. Specifically, the first part of the thesis develops an analytical framework for the modeling, analysis and control of capacitated re-entrant lines, which is based on Generalized Stochastic Petri nets (GSPN) framework. The corresponding scheduling problem is systematically formulated, and the structure of the optimal policy is characterized and compared to that identified for "traditional" re-entrant lines. The second part of thesis addresses the problem of developing a systematic an

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Gibellato, Marilisa Gail. "Stochastic modeling of the sleep process." The Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=osu1110318321.

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Books on the topic "Generalized stochastic processes"

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Schäffler, Stefan. Generalized Stochastic Processes. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78768-8.

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Donatelli, S. A comparison of performance evaluation process algebra and generalized stochastic Petri nets. Computer Systems Group, University of Edinburgh, 1994.

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Yu, Korolev Victor, ed. Generalized poisson models and their applications in insurance and finance. VSP, 2002.

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Stannat, Wilhelm. The theory of generalized Dirichlet forms and its applications in analysis and stochastics. American Mathematical Society, 1999.

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Schäffler, Stefan. Generalized Stochastic Processes: Modelling and Applications of Noise Processes. Birkhäuser, 2018.

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Generalized Functionals of Brownian Motion and Their Appliations. World Scientific Publishing Company, 2011.

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Matsoukas, Themis. Generalized Statistical Thermodynamics: Thermodynamics of Probability Distributions and Stochastic Processes. Springer, 2019.

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Mathematical Statistics: Theory and Applications. De Gruyter, 2020.

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Borodin, Alexei, and Leonid Petrov. Integrable probability: stochastic vertex models and symmetric functions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797319.003.0002.

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This chapter presents the study of a homogeneous stochastic higher spin six-vertex model in a quadrant. For this model concise integral representations for multipoint q-moments of the height function and for the q-correlation functions are derived. At least in the case of the step initial condition, these formulas degenerate in appropriate limits to many known formulas of such type for integrable probabilistic systems in the (1+1)d KPZ universality class, including the stochastic six-vertex model, ASEP, various q-TASEPs, and associated zero-range processes. The arguments are largely based on p

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Algebraic And Geometric Aspects Of Integrable Systems And Random Matrices Ams Special Session Algebraic And Geometric Aspects Of Integrable Systems And Random Matrices January 67 2012 Boston Ma. American Mathematical Society, 2013.

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Book chapters on the topic "Generalized stochastic processes"

1

Krée, Paul, and Christian Soize. "Generalized Stochastic Processes." In Mathematics of Random Phenomena. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4770-2_11.

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Rozanov, Yu A. "On generalized stochastic partial differential equations." In Stochastic Processes. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4615-7909-0_33.

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Lee, Yuh-Jia. "Positive Generalized Functions on Infinite Dimensional Spaces." In Stochastic Processes. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4615-7909-0_25.

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DeFacio, B., G. W. Johnson, and M. L. Lapidus. "Feynman’s Operational Calculus As A Generalized Path Integral." In Stochastic Processes. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4615-7909-0_7.

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Buldygin, Valeriĭ V., Karl-Heinz Indlekofer, Oleg I. Klesov, and Josef G. Steinebach. "Generalized Renewal Processes." In Probability Theory and Stochastic Modelling. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99537-3_8.

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Glover, J., M. Rao, and R. Song. "Generalized Schrödinger Semigroups." In Seminar on Stochastic Processes, 1992. Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4612-0339-1_7.

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Hida, Takeyuki. "A role of the Lévy Laplacian in the causal calculus of generalized white noise functionals." In Stochastic Processes. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4615-7909-0_16.

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Oberguggenberger, Michael. "Generalized Functions and Stochastic Processes." In Seminar on Stochastic Analysis, Random Fields and Applications. Birkhäuser Basel, 1995. http://dx.doi.org/10.1007/978-3-0348-7026-9_16.

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Saichev, Alexander I., and Wojbor A. Woyczyński. "Random Distributions: Generalized Stochastic Processes." In Applied and Numerical Harmonic Analysis. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92586-8_17.

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Anastassiou, George A. "Trigonometric Caputo Fractional Approximation of Stochastic Processes." In Generalized Fractional Calculus. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56962-4_15.

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Conference papers on the topic "Generalized stochastic processes"

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Kang, Sinuk. "Kramer's generalized sampling of stochastic processes." In 2015 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2015. http://dx.doi.org/10.1109/sampta.2015.7148888.

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Bedziuk, Nadzeya V., and Aleh L. Yablonski. "Equations in differentials in the algebra of generalized stochastic processes." In Linear and Non-Linear Theory of Generalized Functions and its Applications. Institute of Mathematics Polish Academy of Sciences, 2010. http://dx.doi.org/10.4064/bc88-0-3.

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Bahadori, Mohammad Taha, Yan Liu, and Eric P. Xing. "Fast structure learning in generalized stochastic processes with latent factors." In KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2013. http://dx.doi.org/10.1145/2487575.2487578.

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Wang, Yan. "Simulating Drift-Diffusion Processes With Generalized Interval Probability." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70699.

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The Fokker-Planck equation is widely used to describe the time evolution of stochastic systems in drift-diffusion processes. Yet, it does not differentiate two types of uncertainties: aleatory uncertainty that is inherent randomness and epistemic uncertainty due to lack of perfect knowledge. In this paper, a generalized Fokker-Planck equation based on a new generalized interval probability theory is proposed to describe drift-diffusion processes under both uncertainties, where epistemic uncertainty is modeled by the generalized interval while the aleatory one is by the probability measure. A p

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Eboli, Monica Goes, and Fabio Gagliardi Cozman. "Modeling Automotive Assembly Lines with Generalized Stochastic Petri Nets and Markov Decision Processes with Imprecise Probabilities." In 2008 SAE Brasil Congress and Exhibit. SAE International, 2008. http://dx.doi.org/10.4271/2008-36-0143.

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Mohan, Ashwin, Sandeep Pendyam, Bradley C. Enke, Peter Kalivas, and Satish S. Nair. "Stochastic Model of Glutamatergic PFC-NAc Synapse Predicts Cocaine-Induced Changes in Receptor Occupancy." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2615.

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Neurotransmitter homeostasis in and around synapses involves random processes such as diffusion, molecular binding and unbinding. A three-dimensional stochastic diffusion model of a synapse was developed to provide molecular level details of neurotransmitter homeostasis not predicted by alternative models based on continuum approaches. This framework was used to estimate effective diffusion and provide a more accurate prediction of geometric tortuosity in the perisynaptic region. The stochastic model was used to predict the relative contributions of non-synaptic sources to extracellular concen

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dos Santos, Fernando P., Ângelo P. Teixeira, and C. Guedes Soares. "Maintenance Planning of an Offshore Wind Turbine Using Stochastic Petri Nets With Predicates." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11639.

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Operation and maintenance (O&M) activities have a significant impact on the energy cost for offshore wind turbines. Analytical methods such as reliability block diagrams and Markov processes along with simulation approaches have been widely used in planning and optimizing O&M actions in industrial systems. Generalized stochastic Petri Nets (GSPN) with predicates coupled with Monte Carlo simulation (MCS) are applied in this paper to model the planning of O&M activities of an offshore wind turbine. The merits of GSPN in modeling complex, multi-state and multi-component systems are ad

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To, C. W. S., and M. L. Liu. "Large Geometrically Nonlinear Responses of Discretized Plate Structures Under Nonstationary Random Excitations." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/cie-9061.

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Abstract In the investigation reported here novel techniques for the computation of highly nonlinear response statistics, such as mean square and covariance of generalized displacements of large scale discretized plate and shell structures have been developed. The techniques combine the versatile finite element method and the stochastic central difference method as well as derivatives of the latter such that complex aerospace and naval structures under intensive transient disturbances represented as nonstationary random processes can be considered. The flat triangular plate finite element is o

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Lloyd, George M. "A Kalman Filter Framework for High-Dimensional Sensor Fusion Using Stochastic Non-Linear Networks." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37834.

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The textbook Kalman Filter (LKF) seeks to estimate the state of a linear system based on having two things in hand: a.) a reasonable state-space model of the underlying process and its noise components; b.) imperfect (noisy) measurements obtained from the process via one or more sensors. The LKF approach results in a predictor-corrector algorithm which can be applied recursively to correct predictions from the state model so as to yield posterior estimates of the current process state, as new sensor data are made available. The LKF can be shown to be optimal in a Gaussian setting and is eminen

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White, Langford B., and Francesco Carravetta. "Stochastic realisation and optimal smoothing for Gaussian generalised reciprocal processes." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263692.

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