Parameter estimation of continuous dynamical linear systems given discrete-time observations

We present a computationally efficient scheme for parameter estimation of continuous dynamical linear systems given discrete-time noisy observations. The proposed scheme is optimal in the sense that it converges iteratively to the exact Maximum Likelihood estimate, where each iteration increases the likelihood.