On the characteristics of a class of Gaussian processes within the white noise space setting

Using the white noise space framework, we construct and study a class of Gaussian processes with stationary increments, which include as particular cases the Brownian and fractional Brownian motions. The derivative processes are computed using Hida’s theory of stochastic distributions.