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2017
DOI: 10.1016/j.jmaa.2017.02.008
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Stochastic reaction-diffusion equations on networks with dynamic time-delayed boundary conditions

Abstract: We consider a reaction-diffusion equation on a network subjected to dynamic boundary conditions, with time delayed behaviour, also allowing for multiplicative Gaussian noise perturbations. Exploiting semigroup theory, we rewrite the aforementioned stochastic problem as an abstract stochastic partial differential equation taking values in a suitable product Hilbert space, for which we prove the existence and uniqueness of a mild solution. Eventually, a stochastic optimal control application is studied.

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Cited by 14 publications
(10 citation statements)
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“…, n, will denote vertexes. We refer to [10,11,19], for further details The structure of the graph is based on the incidence matrix Φ := Φ + − Φ − , where the sum is intended componentwise and Φ = (φ i,α ) n×m , together with the incoming incidence matrix Φ + = φ + i,α n×m , and the outgoing incidence matrix Φ − = φ − i,α n×m , where…”
Section: A General Framework For Systemic Risk In Financial Networkmentioning
confidence: 99%
“…, n, will denote vertexes. We refer to [10,11,19], for further details The structure of the graph is based on the incidence matrix Φ := Φ + − Φ − , where the sum is intended componentwise and Φ = (φ i,α ) n×m , together with the incoming incidence matrix Φ + = φ + i,α n×m , and the outgoing incidence matrix Φ − = φ − i,α n×m , where…”
Section: A General Framework For Systemic Risk In Financial Networkmentioning
confidence: 99%
“…where η is defined as in (19). While, the first four integrals in the right hand side of equation ( 28) can be bounded similarly as done proving Lemma 2.5, see (19), the last two terms can be treated exploiting the Young inequality…”
Section: The Optimal Control Problemmentioning
confidence: 99%
“…The present section closely follows in [35,Section. 7], in particular we will consider weak control problems, we refer to [32] for a general treatment of the present notion of control, or [18,19,50,51]. Let us therefore consider the following R−valued controlled delay equation,      dX(t) = (µ(t, X t , X(t)) + F (t, X(t), α(t))) dt+ +σ(t, X(t))dW (t) + R0 γ(t, X(t), z)Ñ (dt, dz) , (X t0 , X(t 0 )) = (x, η) , In what follows we assume µ, σ and γ to satisfy assumptions 2.2, we also require that it exists a constant C σ > 0 such that, for any t ∈ [0, T ] and x ∈ R, |σ −1 (t, x)| ≤ C σ .…”
Section: Application To Optimal Controlmentioning
confidence: 99%