: The contribution concerns the design of a generalised functional-link neural network with internal dynamics and its applicability to system identification by means of multi-input...
Abstract-- Simple and efficient computational algorithms for nonparametric wavelet-based identification of nonlinearities in Hammerstein systems driven by random signals are propos...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
Various techniques of system identification exist that provide a nominal model and an uncertainty bound. An important question is what the implications are for the particular choi...