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A Bayes Formula for Gaussian Noise Processes and its Applications
2000
SIAM Journal of Control and Optimization
An elementary approach is used to derive a Bayes-type formula, extending the Kallianpur-Striebel formula for the nonlinear filters associated with the Gaussian noise processes. In the particular cases of certain Gaussian processes, recent results of Kunita and of Le Breton on fractional Brownian motion are derived. We also use the classical approximation of the Brownian motion by the Ornstein-Uhlenbeck dispersion process to solve the "instrumentability" problem of Balakrishnan. We give precise
doi:10.1137/s0363012998343380
fatcat:krctfid4mfc4rbhjpthwxv53nu