Regularity and Integration Theory for a Class of Stochastic Processes

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Focusing on stochastic processes with stationary increments and spectral density, the book develops a comprehensive integration theory applicable to various significant random processes, including Wiener and fractional Brownian motion. It explores long-range dependence and intermittency effects, providing insights into generalized stochastic integration. This framework is then utilized to derive regularity results and tackle parabolic Volterra problems influenced by random noise, as well as addressing anomalous diffusion impacted by stochastic disturbances at the boundary.