Abstract
In this paper, we present an identification algorithm for discrete-time multiple-input multiple-output (MIMO) state-space models with colored noise observation. It is assumed that the system is the model with the colored noise observation. The parametric discrete-time canonical-formed MIMO state-space model is identified based on Maximum-Likelihood (ML) and Akaike's Information Criterion (AIC). To obtain the maximum-likelihood estimates of the model parameter, we apply Expectation-Maximization (EM) algorithms which are iterative methods such that the choice of the initial estimates is most important. The initial estimates parameter in canonical-formed state-space models are obtained by N4SID [1] methods.
