IDENTIFICATION OF NONLINEAR BLOCK-ORIENTED SYSTEMS BY THE RECURSIVE KERNEL ESTIMATE

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