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Related papers: Stochastic Wiener Filter in the White Noise Space

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The formalism of Wiener filtering is developed here for the purpose of reconstructing the large scale structure of the universe from noisy, sparse and incomplete data. The method is based on a linear minimum variance solution, given data…

Astrophysics · Physics 2009-10-22 S. Zaroubi , Y. Hoffman , K. B. Fisher , O. Lahav

Using the white noise space setting, we define and study stochastic integrals with respect to a class of stationary increment Gaussian processes. We focus mainly on continuous functions with values in the Kondratiev space of stochastic…

Probability · Mathematics 2010-08-03 Daniel Alpay , Haim Attia , David Levanony

Using the white noise setting, in particular the Wick product, the Hermite transform, and the Kondratiev space, we present a new approach to study linear stochastic systems, where randomness is also included in the transfer function. We…

Probability · Mathematics 2008-11-27 Daniel Alpay , David Levanony

With the use of Hida's white noise space theory space theory and spaces of stochastic distributions, we present a detailed analytic continuation theory for classes of Gaussian processes, with focus here on Brownian motion. For the latter,…

Probability · Mathematics 2025-01-27 Luis Daniel Abreu , Daniel Alpay , Tryphon Georgiou , Palle Jorgensen

We develop several results on hitting probabilities of random fields which highlight the role of the dimension of the parameter space. This yields upper and lower bounds in terms of Hausdorff measure and Bessel--Riesz capacity,…

Probability · Mathematics 2010-11-30 Robert C. Dalang , Marta Sanz-Solé

In this paper, we introduce a non-commutative space of stochastic distributions, which contains the non-commutative white noise space, and forms, together with a natural multiplication, a topological algebra. A special inequality which…

Functional Analysis · Mathematics 2013-02-25 Daniel Alpay , Guy Salomon

The aim of this paper is to present an elementary computable theory of probability, random variables and stochastic processes. The probability theory is baed on existing approaches using valuations and lower integrals. Various approaches to…

Probability · Mathematics 2015-10-14 Pieter Collins

We study state space equations within the white noise space setting. A commutative ring of power series in a countable number of variables plays an important role. Transfer functions are rational functions with coefficients in this…

Probability · Mathematics 2009-11-16 D. Alpay , D. Levanony , A. Pinhas

A new method is described for constructing a generalized solution for stochastic differential equations. The method is based on the Cameron-Martin version of the Wiener Chaos expansion and provides a unified framework for the study of…

Probability · Mathematics 2007-05-23 S. V. Lototsky , B. L. Rozovskii

This paper identifies certain interesting mathematical problems of stochastic quantization type in the modeling of Laser propagation through turbulent media. In some of the typical physical contexts the problem reduces to stochastic…

Analysis of PDEs · Mathematics 2023-01-03 Sivaguru S. Sritharan , Saba Mudaliar

By extending \cite{bensoussan2015control}, we implement the proposal of Lions \cite{lions14} on studying mean field games and their master equations via certain control problems on the Hilbert space of square integrable random variables. In…

Optimization and Control · Mathematics 2019-04-01 Alain Bensoussan , P. Jameson Graber , S. C. P. Yam

In this work we are concerned with the study of the strong order of convergence in the averaging principle for slow-fast systems of stochastic evolution equations in Hilbert spaces with additive noise. In particular the stochastic…

Probability · Mathematics 2023-06-07 Filippo de Feo

Given a Gaussian stationary increment processes with spectral density, we show that a Wick-Ito integral with respect to this process can be naturally obtained using Hida's white noise space theory. We use the Bochner-Minlos theorem to…

Probability · Mathematics 2012-02-09 Daniel Alpay , Alon Kipnis

In this paper we develop a framework to extend the theory of generalized stochastic processes in the Hida white noise space to more general probability spaces which include the grey noise space. To obtain a Wiener-It\^o expansion we recast…

Probability · Mathematics 2020-05-19 Daniel Alpay , Paula Cerejeiras , Uwe Kaehler

In this paper we will develop linear and nonlinear filtering methods for a large class of nonlinear wave equations that arise in applications such as quantum dynamics and laser generation and propagation in a unified framework. We consider…

Analysis of PDEs · Mathematics 2025-03-25 Sivaguru S. Sritharan , Saba Mudaliar

By using stochastic calculus for two-parameter processes and chaos expansion into multiple Wiener-It\^o integrals, we define a 2D-stochastic current over the Brownian sheet. This concept comes from geometric measure theory. We also study…

Probability · Mathematics 2012-09-24 Franco Flandoli , Peter Imkeller , Ciprian Tudor

We present a method, based on the Keldysh formalism, for deriving stochastic master equations that describe the non-Markovian dynamics of a quantum system coupled to a Gaussian environment. This approach yields a compact expression for the…

Quantum Physics · Physics 2026-01-21 Vasco Cavina , Antonio D'Abbruzzo , Vittorio Giovannetti

With the use of tensor product of Hilbert space, and a diagonalization procedure from operator theory, we derive an approximation formula for a general class of stochastic integrals. Further we establish a generalized Fourier expansion for…

Mathematical Physics · Physics 2015-05-13 Palle E. T. Jorgensen , Myung-Sin Song

In this article, we have analyzed the full discretization of the Stochastic semilinear Schr\"{o}dinger equation in a bounded convex polygonal domain driven by multiplicative Wiener noise. We use the finite element method for spatial…

Numerical Analysis · Mathematics 2025-04-22 Suprio Bhar , Mrinmay Biswas , Mangala Prasad

We consider a $d$-dimensional random field $u = \{u(t,x)\}$ that solves a non-linear system of stochastic wave equations in spatial dimensions $k \in \{1,2,3\}$, driven by a spatially homogeneous Gaussian noise that is white in time. We…

Probability · Mathematics 2013-10-02 Robert C. Dalang , Marta Sanz-Solé
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