Optimization of the mean-square approximation procedures for iterated Stratonovich stochastic integrals of multiplicities 1 to 3 with respect to components of the multi-dimensional Wiener process based on Multiple Fourier–Legendre series [PDF]
MATEC Web of Conferences, 2022 The article is devoted to approximation of iterated Ito and Stratonovich stochastic integrals of multiplicities 1 to 3 by the method of multiple Fourier–Legendre series.
Kuznetsov Dmitriy, Kuznetsov Mikhail
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Deterministic Bi-Criteria Model for Solving Stochastic Mixed Vector Variational Inequality Problems
Mathematics, 2023 In this paper, we consider stochastic mixed vector variational inequality problems. Firstly, we present an equivalent form for the stochastic mixed vector variational inequality problems.
Meiju Luo, Menghan Du, Yue Zhang
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Journal of Inequalities and Applications, 2022 We stabilize pseudostochastic ( G 1 , G 2 ) $(\mathcal{G}_{1},\mathcal{G}_{2})$ -random operator inequality using a class of stochastic matrix control functions in matrix Menger Banach algebras.
Safoura Rezaei Aderyani +3 more
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Random Perturbation of Invariant Manifolds for Non-Autonomous Dynamical Systems
Mathematics, 2022 Random invariant manifolds are geometric objects useful for understanding dynamics near the random fixed point under stochastic influences. Under the framework of a dynamical system, we compared perturbed random non-autonomous partial differential ...
Tao Jiang, Zhongkai Guo, Xingjie Yan
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L2-convergence of Yosida approximation for semi-linear backward stochastic differential equation with jumps in infinite dimension [PDF]
Arab Journal of Mathematical SciencesPurpose – The main motivation of this paper is to present the Yosida approximation of a semi-linear backward stochastic differential equation in infinite dimension. Under suitable assumption and condition, an L2-convergence rate is established.
Hani Abidi +3 more
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Stochastic approximation versus sample average approximation for Wasserstein barycenters
, 2021 In the machine learning and optimization community, there are two main approaches for the convex risk minimization problem, namely the Stochastic Approximation (SA) and the Sample Average Approximation (SAA).
Dvinskikh, Darina, Darina Dvinskikh
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Stochastic Lie bracket (derivation, derivation) in MB-algebras
Journal of Inequalities and Applications, 2020 By a stochastic controller, we make stable the pseudo stochastic Lie bracket (derivation, derivation) in complex MB-algebras. Next, we get an approximation by a stochastic Lie bracket (derivation, derivation) and calculate the maximum error of the ...
Masoumeh Madadi +3 more
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Best approximation of κ-random operator inequalities in matrix MB-algebras
Journal of Inequalities and Applications, 2021 We introduce a class of stochastic matrix control functions and apply them to stabilize pseudo stochastic κ-random operator inequalities in matrix MB-algebras.
Masoumeh Madadi +3 more
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A Continuous-Time Urn Model for a System of Activated Particles
Mathematics, 2023 We study a system of M particles with jump dynamics on a network of N sites. The particles can exist in two states, active or inactive. Only the former can jump. The state of each particle depends on its position.
Rafik Aguech, Hanene Mohamed
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Efficiency of the stochastic approximation method [PDF]
Yugoslav Journal of Operations Research, 2012 The practical aspect of the stochastic approximation method (SA) is studied. Specifically, we investigated the efficiency depending on the coefficients that generate the step length in optimization algorithm, as well as the efficiency depending on the
Japundžić Miloš
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