Risk-sensitive filtering and smoothing for continuous-time Markov processes
We consider risk sensitive filtering and smoothing for a dynamical system whose output is a vector process in ℝ2. The components of the observation process are a Markov process observed through a Brownian motion and a Markov process observed through a P
|Collections||ANU Research Publications|
|Source:||IEEE Transactions on Information Theory|
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