Maximum likelihood least squares iterative identification algorithm for hammerstein output error moving average systems

This paper studies the parameter estimation problem of Hammerstein output error moving average (OEMA) systems. According to the maximum likelihood principle and iterative identification technique, a maximum likelihood least squares iterative identification (ML-LSI) algorithm is proposed. A numerical example is provided to verify the effectiveness of the proposed algorithm.