Iterative and recursive subspace algorithms for identification of Hammerstein model with SH nonlinearity

This paper proposes a new method to estimate the parameters of both blocks, linear and nonlinear using an iterative and recursive subspace approaches. More importantly, in an attempt to show the extent to which this method is efficient, the numerical example confirms a good conditioning and computational efficiency.