Titlebook: Stochastics in Finite and Infinite Dimensions; In Honor of Gopinath Takeyuki Hida,Rajeeva L. Karandikar,Jie Xiong Book 2001 Birkhäuser Bost

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Hidden Markov Chain Filtering for Generalised Bessel Processes,fusion coefficient in (1.1) does not depend on R. and the drift coefficient is linear in R. and.. We also observe that for a. 0 we have an Ornstein-Uhlenbeck process. Under the condition.And c. > 0, the generalized Bessel process can be shown to remain strictly positive for . >0, a feature which makes it attractive for many applications.

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On Equations of Stochastic Fluid Mechanics,rticular cases the deterministic Navier-Stokes and Euler equations as well as these equations with stochastic forcing We also discuss existence of global weak solutions of the stochastic Navier-Stokes equation in R. for d = 2, 3. Uniqueness of a solution is established in the case d=2.

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Monte Carlo Algorithms and Asymptotic Problems in Nonlinear Filtering,r, perhaps, combinations of sampling and analytical methods) become attractive. Extensions of the previous work to a wide class of such algorithms is dealt with, with similar results. For brevity, we confine ourselves to discrete time, but the same results hold for the continuous time case [.].

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Random Iteration of I.I.D. Quadratic Maps,Let,and be an i,i.d. sequence with values in [0, .]. Let be a Markov chain defined by the random iteration scheme.In this paper we present a survey of recent results on the existence and uniqueness of nontrivial invariant probability measures for. A brief review of the deterministic case is also included.

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https://doi.org/10.1007/978-1-4612-0167-0Gaussian process; Kernel; Likelihood; Markov; algorithm; algorithms; calculus; differential equation; filter

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