Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels Vrije Universiteit Brussel KU Leuven
Providing flexibility and user-interpretability in nonlinear system identification can be achieved by means of block-oriented methods. One of such block-oriented system structures is the parallel Wiener-Hammerstein system, which is a sum of Wiener-Hammerstein branches, consisting of static nonlinearities sandwiched between linear dynamical blocks. Parallel Wiener-Hammerstein models have more descriptive power than their single-branch ...