Least-squares estimation has always been the main approach when applying prediction error methods (PEM) in the identification of linear dynamical systems. Regardless of the estim...
The adaptive estimation of a time-varying parameter vector in a linear Gaussian model is considered where we a priori know that the parameter vector belongs to a known arbitrary s...
— State estimation is addressed for a class of discrete-time systems that may switch among different modes taken from a finite set. The system and measurement equations of each ...
Angelo Alessandri, Marco Baglietto, Giorgio Battis...
Training sequences for estimation of channel parameters have been well designed under the condition that the number of the unknown channel parameters is not greater than the numbe...
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...