Identification of nonlinear block-oriented systems by the recursive kernel estimate

Abstract

The identification of block-oriented systems by the kernel recursive estimate is discussed. Three types of system are considered: cascade of nonlinear memoryless system, Hammerstein system and Wiener system. The optimal model of memoryless cascade system is derived and estimated by the recursive kernel regression estimate. Nonlinear dynamical systems of Hammerstein and Wiener type with arbitrary nonlinearities are identified by means of nonparametric techniques. Convergence of identification procedures is investigated.