  A new approach for signal parametrization, which consists of a specific
regression model incorporating a discrete hidden logistic process, is proposed.
The model parameters are estimated by the maximum likelihood method performed
by a dedicated Expectation Maximization (EM) algorithm. The parameters of the
hidden logistic process, in the inner loop of the EM algorithm, are estimated
using a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm. An
experimental study using simulated and real data reveals good performances of
the proposed approach.
