Electronic Communications in Probability · 1998 · 69 citations · 7 references
EngineeringMathematicsPhysicsProbability TheoryStochastic ModelingStochastic ProcessesBrownian MotionErgodic TheoryGaussian ProcessesLong-memory ProcessesMarkov ProcessesStochastic CalculusBrownian Motion ApproximationsErgodic ProcessesFractional Brownian MotionLinear FunctionalsLong Memory ModelsMarkov-process Approximation
Fractional Brownian motion belongs to a class of long memory Gaussian processes that can be represented as linear functionals of an infinite dimensional Markov process. This leads naturally to: An efficient algorithm to approximate the process.An ergodic theorem which applies to functionals of the type $$\int_0^t \phi(V_h(s)),ds \quad\text{where}\quad V_h(s)=\int_0^s h(s-u), dB_u,.$$ where $B$ is a real Brownian motion.
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