On Recursive parametric Identification of Wiener Systems

The aim of the given paper is the development of a recursive approach for parametric identification of Wiener systems with non-invertible piecewise linear function inr the nonlinear block. It is shown here that the problem of parametric identification of a Wiener system could be reduced to a linear parametric estimation problem by a simple input-output data reordering and by a following data partition. An approach based on sequential reconstruction of the values of intermediate signal by following use of the ordinary recursive least squares (RLS) is proposed here for the estimation of parameters of linear and nonlinear parts of the Wiener system. The unknown threshold of piecewise nonlinearity has been estimated by processing recursively respective particles of current input-output data, too. The results of numerical simulation and parametric estimation of Wiener systems with different piecewise nonlinearities by computer are given.