  This paper proposes a general switching dynamical system model, and a custom
majorization-minimization-based algorithm EM++ for identifying its parameters.
For certain families of distributions, such as Gaussian distributions, this
algorithm reduces to the well-known expectation-maximization method. We prove
global convergence of the algorithm under suitable assumptions, thus addressing
an important open issue in the switching system identification literature. The
effectiveness of both the proposed model and algorithm is validated through
extensive numerical experiments.
