scholarly journals Stochastic Volterra equations driven by cylindrical Wiener process

2007 ◽  
Vol 7 (2) ◽  
pp. 373-386 ◽  
Author(s):  
Anna Karczewska ◽  
Carlos Lizama
2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Gregorio Díaz ◽  
Jesús Ildefonso Díaz

<p style='text-indent:20px;'>We consider a class of one-dimensional nonlinear stochastic parabolic problems associated to Sellers and Budyko diffusive energy balance climate models with a Legendre weighted diffusion and an additive cylindrical Wiener processes forcing. Our results use in an important way that, under suitable assumptions on the Wiener processes, a suitable change of variables leads the problem to a pathwise random PDE, hence an essentially "deterministic" formulation depending on a random parameter. Two applications are also given: the stability of solutions when the Wiener process converges to zero and the asymptotic behaviour of solutions for large time.</p>


2017 ◽  
Vol 10 (07) ◽  
pp. 1750103 ◽  
Author(s):  
S. Singh ◽  
S. Saha Ray

In this paper, numerical solutions of the stochastic Fisher equation have been obtained by using a semi-implicit finite difference scheme. The samples for the Wiener process have been obtained from cylindrical Wiener process and Q-Wiener process. Stability and convergence of the proposed finite difference scheme have been discussed scrupulously. The sample paths obtained from cylindrical Wiener process and Q-Wiener process have also been shown graphically.


Author(s):  
CHRISTIAN OLIVERA

Following the ideas of F. Russo and P. Vallois, we use the notion of forward integral to introduce a new stochastic integral respect to the cylindrical Wiener process. This integral is an extension of the classical integral. As an application, we prove existence of solution of a parabolic stochastic differential partial equation with anticipating stochastic initial date.


2020 ◽  
Vol 18 (4) ◽  
pp. 122-131
Author(s):  
Vadim F. Islamutdinov ◽  
Sergey P. Semenov

The purpose of the study is to develop a model for the co-evolution of the regional economy and economic institutions. The research methods used: abstract-logical for the study of theoretical aspects and the experience of modeling co-evolution; and economic-mathematical for the development of own model of coevolution. The results of the study: approaches to modeling the evolution of economic institutions, as well as the co-evolution of the regional economy and economic institutions are considered, strengths and weaknesses of existing approaches to modeling co-evolution are identified, on the basis of the logistic model and Lotka-Volterra equations, an own co-evolution model has been developed, which includes three entities: regional economy, “good” institution and “bad” institution. Three versions of the model have been developed: the co-evolution of the regional economy and the “good” institution, the co-evolution of the regional economy and the “bad institution,” and a variant of the co-evolution of all three entities simultaneously, in which the “good” and “bad” institutions interact according to the “predator-prey” model, and their the cumulative effect determines the development of the regional economy. Numerical experiments have been carried out in the MathLab, which have shown the capabilities of the model to reflect the results of the co-evolution of the economy of a resource-producing region and economic institutions. In the first variant, a “good” institution promotes economic growth in excess of the level determined by resource availability. In the second variant, the “bad” institution has a disincentive effect on the GRP, as a result of which the GRP falls below the level determined by the resource endowment. In the third variant, the interaction of “good” and “bad” institutions still contributes to economic growth above the level determined by resource availability, but causes cyclical fluctuations in the GRP.


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