On system identification for ARMAX models based on the variational Bayesian method

This paper proposes a parameter estimation method for ARMAX models based on the variational Bayesian method. In order to obtain the posterior distribution in an exact form, we convert the original estimation problem into another one in which the equation to be solved is linear in the unknown parameter by employing an artificial unknown parameter. Then the resulting estimation algorithm is derived based on the constrained optimization technique.