“…The analysis is based on the results of the deterministic problem (15). First, we present mild and strong solvability results and then, by Remark 1 and the assumption A(3)(ii), we prove the well posedness of problem (5).…”
Section: The Forward Stochastic Problemmentioning
confidence: 99%
“…For the treatment of the solvability problem one can see [1], [13], [19]. Additionally, the backward problem and the exact controllability of the stochastic descriptor equations (2), (3), have been studied only recently in [13,15]. In this paper, more general equations of the form (4), In infinite dimensions, interesting applications of degenerate equations (4) (or (1)) are obtained if the operator M is a differential and L is a multiplicative one with a function that vanishes in a certain region of the configuration space.…”
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.
“…The analysis is based on the results of the deterministic problem (15). First, we present mild and strong solvability results and then, by Remark 1 and the assumption A(3)(ii), we prove the well posedness of problem (5).…”
Section: The Forward Stochastic Problemmentioning
confidence: 99%
“…For the treatment of the solvability problem one can see [1], [13], [19]. Additionally, the backward problem and the exact controllability of the stochastic descriptor equations (2), (3), have been studied only recently in [13,15]. In this paper, more general equations of the form (4), In infinite dimensions, interesting applications of degenerate equations (4) (or (1)) are obtained if the operator M is a differential and L is a multiplicative one with a function that vanishes in a certain region of the configuration space.…”
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.
“…Suppose that x 2 (t) is the inverse stochastic Laplace transform of X 2 (s) obtained from (7). Then, x 2 (t) is the impulse solution to (6) in the sense of the stochastic Laplace transform, or simply, the impulse solution to (6). In this case, if x 1 (t) denotes the solution to (5), then…”
Section: Let [mentioning
confidence: 99%
“…Using white noise and fractional white noise, two illustrative applications are presented in a previously conducted study [2]. The basic question of solvability has been formulated and considered [5,6]. Moreover, they propose a normalization procedure, and they completely solve the problem of exact controllability for a class of linear stochastic singular systems.…”
“…for all y 1 , y 2 ∈ R d , z 1 , z 2 ∈ R d×k , (t, ω) a.e.. Since then, the BSDEs have been studied extensively, and have found wide applicability in areas such as mathematical finance, stochastic control, and stochastic controllability; see, for example, [10], [17], [29], [31], [42], [37], [20], [21], [22] [41], and the references therein. One direction of research has been to weaken the assumption of global Lipschitz condition (2) by assuming only local Lipschitz condition (see [1]), or non-Lipschitz condition of a particular form (see [30], [39]).…”
In this paper we consider two classes of backward stochastic differential equations. Firstly, under a Lipschitz-type condition on the generator of the equation, which can also be unbounded, we give sufficient conditions for the existence of a unique solution pair. The method of proof is that of Picard iterations and the resulting conditions are new. We also prove a comparison theorem. Secondly, under the linear growth and continuity assumptions on the possibly unbounded generator, we prove the existence of the solution pair. This class of equations is more general than the existing ones.
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