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

A regression model with a hidden logistic process for signal parametrization