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Maximum Likelihood Parameter Estimation for Systems with Noisy Dynamics and Observations

C.D. Charalambous, R.J. Elliott, V. Krishnamurthy

This project is concerned with estimating unknown parameters for continuous-times systems which are subject to noisy dynamics and observations. In the special case of Gauss-Markov systems, the parameters entering the Kalman-Filter are estimated via Maximum-Likelihood techniques using the Expectation-Maximization algorithm.
 


Annual Report

Fri Nov 26 23:00:32 GMT 1999