Add to ORKGThe main notions and tools from white noise analysis are set up on the basis of the calculus of Gaussian random variables and the S-transform. A new proof of the formula for the S-transform of Itô integrals is given. Moreover, measurability and the martingale property with respect to the Brownian filtration are characterized in terms of the S-transform. This allows to extend these notions to random variables and processes, respectively, in the space of Hida distributions
We introduce the concept of functional process and consider the stochastic boundary value problem an...
In this paper we show that for any spatial dimension the renormalized self-intersection local times ...
AbstractIn this paper we will set up the Hida theory of generalized Wiener functionals using S∗(Rd),...
The main notions and tools from white noise analysis are set up on the basis of the calculus of Gaus...
White noise is often regarded as the informal nonexistent derivative B˙(t) of a Brownian motion B˙(t...
This thesis consists of two parts, each part concentrating on a different problem from the theory of...
AbstractEmploying the Segal–Bargmann transform (S-transform for abbreviation) of regular Lévy white ...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
In White Noise Analysis (WNA), various random quantities are analyzed as Hida distributions ([1]). T...
Given a Gaussian stationary increment processes, we show that a Skorokhod-Hitsuda stochastic integra...
In this paper we will set up the Hida theory of generalized Wiener functionals using *(d), the space...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
In this paper we develop a framework to extend the theory of generalized stochastic processes in the...
We prove the white noise generalization of the Clark-Ocone formula under change of measure by using ...
We introduce the concept of functional process and consider the stochastic boundary value problem an...
In this paper we show that for any spatial dimension the renormalized self-intersection local times ...
AbstractIn this paper we will set up the Hida theory of generalized Wiener functionals using S∗(Rd),...
The main notions and tools from white noise analysis are set up on the basis of the calculus of Gaus...
White noise is often regarded as the informal nonexistent derivative B˙(t) of a Brownian motion B˙(t...
This thesis consists of two parts, each part concentrating on a different problem from the theory of...
AbstractEmploying the Segal–Bargmann transform (S-transform for abbreviation) of regular Lévy white ...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
In White Noise Analysis (WNA), various random quantities are analyzed as Hida distributions ([1]). T...
Given a Gaussian stationary increment processes, we show that a Skorokhod-Hitsuda stochastic integra...
In this paper we will set up the Hida theory of generalized Wiener functionals using *(d), the space...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
In this paper we develop a framework to extend the theory of generalized stochastic processes in the...
We prove the white noise generalization of the Clark-Ocone formula under change of measure by using ...
We introduce the concept of functional process and consider the stochastic boundary value problem an...
In this paper we show that for any spatial dimension the renormalized self-intersection local times ...
AbstractIn this paper we will set up the Hida theory of generalized Wiener functionals using S∗(Rd),...