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Linear stochastic degenerate Sobolev equations and applications

机译:线性随机简并Sobolev方程和应用

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摘要

In this paper, a general class of linear stochastic degenerate Sobolev equations with additive noise is considered. This class of systems is the infinite-dimensional analogue of linear descriptor systems in finite dimensions. Under appropriate assumptions, the mild and strong well-posedness for the initial value problem are studied using elements of the semigroup theory and properties of the stochastic convolution. The final value problem is also examined and it is proved that this is uniquely strongly solvable and the solution is continuously dependent on the final data. Based on the results of the forward and backward problem, the conditions for the exact controllability are investigated for a special but important class of these equations. The abstract results are illustrated by applications in complex media electromagnetics, in the one-dimensional stochastic Dirac equation in the non-relativistic limit and in a potential application in input-output analysis in economics.
机译:在本文中,考虑了具有加性噪声的一类一般的线性随机退化Sobolev方程。这类系统是有限维线性描述符系统的无穷大模拟。在适当的假设下,使用半群论的要素和随机卷积的性质研究了初值问题的适度和强适定性。还研究了最终值问题,并证明了这是唯一可强求解的,并且解决方案一直取决于最终数据。根据向前和向后问题的结果,研究了这些方程的特殊但重要的一类的精确可控制性的条件。通过在复杂介质电磁学中的应用,在非相对论极限中的一维随机Dirac方程以及在经济学中的投入产出分析中的潜在应用,可以说明抽象的结果。

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