Time-domain identification using ARMARKOV/Toeplitz models

Recursive time-domain identification techniques using a recursive least-squares algorithm with an ARMA representation have been used to identify the transfer function coefficients of SISO systems. In this paper we derive an alternative recursive time-domain identification technique that is based upon recursive identification of the Markov parameters of a system. We introduce the recursive ARMARKOV/Toeplitz identification algorithm which estimates the Markov parameters recursively from time-domain input-output data. This identification technique is based upon linear time-invariant finite-dimensional systems having an ARMARKOV representation that relates the current output of a system to past outputs as well as current and past inputs.