Computational algorithms for multiscale identification of nonlinearities in Hammerstein systems with random inputs

There are well-known procedures for computing values of compactly supported wavelets in binary grid points. Such algorithms are inherently well suited for solving system identification tasks with fixed input design. We show that they can be also efficiently used for the solution of system identification problems with random x-variables.