In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...
Abstract: It is often challenging to reconstruct accurately a complete dynamic biological network due to the scarcity of data collected in cost-effective experiments. This paper ad...
We describe the use of the discrete wavelet transform (DWT) for non-parametric linear time-invariant system identification. Identification is achieved by using a test excitation t...
Identification of time-varying linear systems, which introduce both time-shifts (delays) and frequency-shifts (Doppler-shifts), is a central task in many engineering applications...
Ellipsoidal outer-bounding of the set of all feasible state vectors under model uncertainty is a natural extension of state estimation for deterministic models with unknown-but-bo...