Perturbation signals for system identification
Perturbation signals for system identification
Brief Frequency response function measurements in the presence of nonlinear distortions
Automatica (Journal of IFAC)
On linear models for nonlinear systems
Automatica (Journal of IFAC)
Technical Communique: Generation of enhanced initial estimates for Hammerstein Systems
Automatica (Journal of IFAC)
Least-squares LTI approximation of nonlinear systems and quasistationarity analysis
Automatica (Journal of IFAC)
Linear approximations of nonlinear FIR systems for separable input processes
Automatica (Journal of IFAC)
Identification of linear systems with nonlinear distortions
Automatica (Journal of IFAC)
Hammerstein-Wiener system estimator initialization
Automatica (Journal of IFAC)
Elliptically symmetric distributions
IEEE Transactions on Information Theory
| Hi-index | 22.14 |
Random multisines have successfully been used as input signals in many system identification experiments. In this paper, it is shown that scalar random multisine signals with a flat amplitude spectrum are separable of order one. The separability property means that certain conditional expectations are linear and it implies that random multisines can easily be used to obtain accurate estimates of the linear time-invariant part of a Hammerstein system. Furthermore, higher order separability is investigated.