The two most commonly used

stochastic integral types are the Ito integral (Ito 1951) and the Stratonovich integral (Stratonovich 1966).

They cover the

stochastic integral and Itf formula,Ornstein-Uhlenbeck processes and stochastic differential equations, and random attractors.

infinity]] (I, E) in the sense that it satisfies the following

stochastic integral equation:

In this case, the main problem is a concept of a fuzzy

stochastic integral which should cover the notion of the classical stochastic Ito integral.

in which X is a real martingale and Y is the

stochastic integral, with respect to X, of a certain predictable process H = [([H.

Nayak, Pattanayak and Mishra [1] proved that the random Fourier-Stieltjes series(RFS) (1 ) converges in probability to the

stochastic integralSince the

stochastic integral on the right-hand side of Eq.

2]), in paper [1] we could avoid the use of the

stochastic integral to obtain some results from stochastic calculus, e.

X [OMEGA] [right arrow] X, x [member of] X, satisfying the

stochastic integral equation:

He will present, "FastSies: A Fast

Stochastic Integral Equation Solver for Modeling the Rough Surface Effects," during the Silicon Valley Chapter of the IEEE Solid State Circuits Society Monday, May 15, at 7 p.

On the other hand as far as we know there are only few papers dealing with

stochastic integral inclusions driven by random fields (see [25], [26], [47]).

The forward looking

stochastic integral in discrete time of a process H with respect to a process S is defined by