Academic literature on the topic 'G-stochastic integral'

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Journal articles on the topic "G-stochastic integral"

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Guo, C., S. Fang, Y. He, and Y. Zhang. "Stochastic Calculus for Fractional G-Brownian Motion and its Application to Mathematical Finance." Markov Processes And Related Fields, no. 2024 № 4 (30) (February 8, 2025): 477–524. https://doi.org/10.61102/1024-2953-mprf.2024.30.4.002.

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Recently, a new concept for some stochastic process called fractional G-Brownian motion (fGBm) was developed. Compared to the standard Brownian motion, fractional Brownian motion and G-Brownian motion, the fGBm can exhibit long-range dependence and feature volatility uncertainty simultaneously. Thus it generalizes the concepts of the former three processes, and can be a better alternative stochastic process in real applications. In this paper, some stochastic calculus for the fGBm is established and its application to mathematical finance is discussed. First some stochastic integrals with resp
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HERNÁNDEZ, JORGE ELIECER. "ON (m, h1, h2)-G-CONVEX DOMINATED STOCHASTIC PROCESSES." Kragujevac Journal of Mathematics 46, no. 2 (2022): 215–27. http://dx.doi.org/10.46793/kgjmat2202.215h.

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In this paper is introduced the concept of (m, h1, h2)-convexity for stochastic processes dominated by other stochastic processes with the same property, some mean square integral Hermite-Hadamard type inequalities for this kind of generalized convexity are established and from the founded results, other mean square integral inequalities for the classical convex, s-convex in the first and second sense, P-convex and MT-convex stochastic processes are deduced.
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El-Sayed, A. M. A., M. Abdurahman, and H. A. Fouad. "Existence and stability results for the integrable solution of a singular stochastic fractional-order integral equation with delay." Journal of Mathematics and Computer Science 33, no. 01 (2023): 17–26. http://dx.doi.org/10.22436/jmcs.033.01.02.

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In this paper, we are concerning with the existence of the solution \( \V \in L_1([0,\tau],L_2(\Omega))\) of the singular stochastic fractional-order integral equation with delay \(\varrho(.) \), \[ \V(t) = B(t) t^{\alpha - 1} + \lambda ~ \I^{\beta} \G(t,\V(\varrho (t))), ~~~t\in (0,\tau], \] where \(B(t)\) is a given second order mean square stochastic process, \( \lambda \) is a parameter, \(\varrho (t) \leq t\), and \(\G(t,\V) \) is a measurable function in \(t \in (0,\tau]\) and satisfies Lipschitz condition on the second argument. %and \(x\in C_{1-\beta}([0,T],L_2(\Omega)) $ will be prove
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Choi, Jae. "Conditional wiener integral associated with Gaussian processes and applications." Filomat 37, no. 26 (2023): 8791–811. http://dx.doi.org/10.2298/fil2326791c.

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Let C0[0,T] denote the one-parameter Wiener space and let C?0[0,T] be the Cameron-Martin space in C0[0,T]. Given a function k in C?0[0,T], define a stochastic process Zk : C0[0,T] ? [0, T] ? R by Zk(x, t) = R t 0 Dk(s)dx(s), where Dk ? d/dt k. Let a random vector XG,k : C0[0,T] ? Rn be given by XG,k(x) = ((g1,Zk(x,?))~,..., (gn,Zk(x,?))~), where G = {g1, ..., gn} is an orthonormal set with respect to the weighted inner product induced by the function k on the space C?0[0,T], and (g,Zk(x,?))~ denotes the Paley-Wiener-Zygmund stochastic integral. In this paper, using the reproducing kernel prope
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Aoyama, Takahiro, та Makoto Maejima. "Characterizations of subclasses of type G distributions on $ℝ^d$ by stochastic integral representations". Bernoulli 13, № 1 (2007): 148–60. http://dx.doi.org/10.3150/07-bej5136.

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Cuong, Dang Kien, Duong Ton Dam, Duong Ton Thai Duong, and Du Thuan Ngo. "Solutions to the jump-diffusion linear stochastic differential equations." Science and Technology Development Journal - Natural Sciences 3, no. 2 (2019): 115–19. http://dx.doi.org/10.32508/stdjns.v3i2.663.

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The jump-diffusion stochastic process is one of the most common forms in reality (such as wave propagation, noise propagation, turbulent flow, etc.), and researchers often refer to them in models of random processes such as Wiener process, Levy process, Ito-Hermite process, in research of G. D. Nunno, B. Oksendal, F. B. Hanson, etc. In our research, we have reviewed and solved three problems: (1) Jump-diffusion process (also known as the Ito-Levy process); (2) Solve the differential equation jump-diffusion random linear, in the case of one-dimensional; (3) Calculate the Wiener-Ito integral to
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Ma, Li, and Yujing Li. "Stability Analysis of Stochastic Differential Equation Driven by G-Brownian Motion under Non-Lipschitz Condition." Mathematical Problems in Engineering 2022 (September 1, 2022): 1–16. http://dx.doi.org/10.1155/2022/7592535.

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This paper is devoted to studying the p-th moment exponential stability for a class of stochastic differential equation (SDE) driven by G-Brownian motion under non-Lipschitz condition. The delays considered in this paper are time-varying delays τ i t 1 ≤ i ≤ 3 . Since the coefficients are non-Lipschitz, the normal enlargement on the coefficients is not available and the Gronwall inequality is not suitable in this case. By Bihari inequality and Itô integral formula, it is pointed out that there exists a constant τ ∗ such that the p-th moment exponential stability holds if the time-varying delay
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Noeiaghdam, Samad, and Mohammad Ali Fariborzi Araghi. "A Novel Algorithm to Evaluate Definite Integrals by the Gauss-Legendre Integration Rule Based on the Stochastic Arithmetic: Application in the Model of Osmosis System." Mathematical Modelling of Engineering Problems 7, no. 4 (2020): 577–86. http://dx.doi.org/10.18280/mmep.070410.

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Finding the optimal iteration of Gaussian quadrature rule is one of the important problems in the computational methods. In this study, we apply the CESTAC (Controle et Estimation Stochastique des Arrondis de Calculs) method and the CADNA (Control of Accuracy and Debugging for Numerical Applications) library to find the optimal iteration and optimal approximation of the Gauss-Legendre integration rule (G-LIR). A theorem is proved to show the validation of the presented method based on the concept of the common significant digits. Applying this method, an improper integral in the solution of th
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Zhang, Yunlong, Weizhi Xu, Dongsheng Du, and Shuguang Wang. "Stochastic Optimization of Dissipation Structures Based on Lyapunov Differential Equations and the Full Stress Design Method." Buildings 13, no. 3 (2023): 665. http://dx.doi.org/10.3390/buildings13030665.

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This article presents a Lyapunov precise integral-based analysis method for seismic structures with added viscous fluid dampers. This study uses the full stress algorithm as the optimization method, considering the mean square of interstory drifts as the optimization objective, the position of the damper as the optimization object, and the random vibration analysis method as the calculation method to optimize seismic frame structures with viscous dampers. A precise integral solution is derived for the Lyapunov equation based on the general expression of the Lyapunov differential equation for t
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Yukich, J. E. "The convolution metric dg." Mathematical Proceedings of the Cambridge Philosophical Society 98, no. 3 (1985): 533–40. http://dx.doi.org/10.1017/s0305004100063738.

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SummaryWe introduce and study a new metric on denned bywhere is the space of probability measures on ℝk and where g: ℝk→ is a probability density satisfying certain mild conditions. The metric dg, relatively easy to compute, is shown to have useful and interesting properties not enjoyed by some other metrics on . In particular, letting pn denote the nth empirical measure for P, it is shown that under appropriate conditions satisfies a compact law of the iterated logarithm, converges in probability to the supremum of a Gaussian process, and has a useful stochastic integral representation.
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Dissertations / Theses on the topic "G-stochastic integral"

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IBRAGIMOV, ANTON. "G - Expectations in infinite dimensional spaces and related PDES." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/44738.

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In this thesis, we extend the G-expectation theory to infinite dimensions. Such notions as a covariation set of G-normal distributed random variables, viscosity solution, a stochastic integral drive by G-Brownian motion are introduced and described in the given infinite dimensional case. We also give a probabilistic representation of the unique viscosity solution to the fully nonlinear parabolic PDE with unbounded first order term in Hilbert space in terms of G-expectation theory.
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Conference papers on the topic "G-stochastic integral"

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Ubani, Ephraim, Darius Shahsavari, and Lester Duruewuru. "Integrated Reservoir Evaluation and Simulation Study of the Northeast Alamein Field: A Field Case Study." In Mediterranean Offshore Conference. SPE, 2024. http://dx.doi.org/10.2118/223277-ms.

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Abstract The Northeast Alamein (NEAL) field, discovered in August 2010 with the drilling of NEAL-1X well, is an integral part of the Yidma-Alamein concession in the Western Desert of Egypt and is located about 3 km to the northeast direction from the Alamein oil field. Eighteen wells, a mix of vertical and horizontal, have been drilled in the field. The NEAL field is one of the primary oil producers of the concession and of the estimated 42.7 MMSTB of OOIP, the current recovery factor is about 12.0 percent. The objective of the study of the NEAL field was to develop a better understanding of t
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