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An EM Algorithm for Lebesgue-sampled State-space Continuous-time System Identification
This paper concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling.
On Recursive State Estimation for Linear State-Space Models Having Quantized Output Data
We consider a new approach based on the Gaussian sum filter/smoother where the probability mass function of the quantized data given the state is modeled as an integral equation and approximated using Gauss-Legendre quadrature.
A MAP approach for $\ell_q$-norm regularized sparse parameter estimation using the EM algorithm
In this paper, Bayesian parameter estimation through the consideration of the Maximum A Posteriori (MAP) criterion is revisited under the prism of the Expectation-Maximization (EM) algorithm.
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