Parameter estimation in stochastic systems: some recent results and applications

Some recent work on the characterization of almost sure limit sets for maximum likelihood estimates for stochastic systems is reviewed. Applications to allied topics such as input selection for identification, model selection, self-tuning etc. are briefly discussed

Controlled diffusion processes

This article gives an overview of the developments in controlled diffusion processes, emphasizing key results regarding existence of optimal controls and their characterization via dynamic programming for a variety of cost criteria and structural assumptions. Stochastic maximum principle and control under partial observations (equivalently, control of nonlinear filters) are also discussed. Several other related topics are briefly sketched.Comment: Published at http://dx.doi.org/10.1214/154957805100000131 in the Probability Surveys (http://www.i-journals.org/ps/) by the Institute of Mathematical Statistics (http://www.imstat.org

Pathwise smoothing of Markov processes with noisy observations

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