Algorithm and simulation research for blind nonlinear system identification

Abstract

Aiming at solving the blind discrete nonlinear system identification problem, a cyclostationarity-based blind identification method of nonlinear system is proposed. In order to turn the identification process with input into the process without input, the first-order statistical characteristics of cyclostationary input and the inverse nonlinear mapping of the Hammerstein-Wiener model are introduced. The paper describes the statistical characteristics of the input and the structure of Hammerstein-Wiener model, and then discusses the mechanism of blind identification algorithm. Simulation results demonstrate the effectiveness of this approach in solving a class of discrete nonlinear system blind identification. © 2010 Springer-Verlag Berlin Heidelberg.